What we got from the Predicting Red Hat Business Value competitionUmaporn Kerdsaeng
This slide is to share what I've learned from the kaggle competition. There 3 topics -1) Overview of the competition 2) Introduction to Decision Tree and 3) R package XGboost.
Jonathan Lefman presents his work on Superresolution chemical microscopyJonathan Lefman
This document discusses several microscopy techniques including structured illumination fluorescence microscopy, time-of-flight secondary ion mass spectrometry, coherent anti-Stokes Raman scattering microscopy, photoactivated localization microscopy, stimulated emission depletion microscopy, and 4Pi microscopy. It focuses on describing improvements made to structured illumination fluorescence microscopy including parallel GPU processing to accelerate image analysis and a new automated imaging framework. Time-of-flight secondary ion mass spectrometry imaging is discussed with applications to iterative clustering and classification analysis.
The document discusses various disk scheduling algorithms used by operating systems to optimize disk access time and efficiency. It describes common algorithms like First Come First Serve (FCFS), Shortest Seek Time First (SSTF), SCAN, C-SCAN, LOOK, and C-LOOK. For each algorithm, it provides an example to calculate the total seek length for a sample request queue. It then compares the performance of the different algorithms based on total and average seek lengths. In conclusion, it notes that SCAN and C-SCAN work best under heavy disk loads while SSTF and LOOK are commonly used default algorithms.
Dr. Kashif Rasul from Zalando Research in Berlin held this presentation on "Multi-GPU for Deep Learning" on the COMPUTER SCIENCE, MACHINE LEARNING & STATISTICS MEETUP in the Zalando adtech lab Office in Hamburg on 6th September 2017
This document describes implementing a modified particle filter algorithm for localization in an FPGA. The modified algorithm improves speed and accuracy. It was tested through simulations of global localization, localization and tracking, and kidnapping scenarios. The hardware implementation was 34x faster than software and successfully localized the robot in all experiments, demonstrating the FPGA is capable of running the particle filter in real-time.
NUMA-optimized Parallel Breadth-first Search on Multicore Single-node SystemYuichiro Yasui
The document proposes a NUMA-optimized parallel breadth-first search (BFS) algorithm for multicore systems. It discusses how the hybrid BFS algorithm combines top-down and bottom-up approaches but can result in unnecessary edge traversals. The proposal distributes the graph columns to each NUMA node's local memory and binds threads and data to improve locality. It uses a library called ULIBC to intelligently manage CPU affinity and NUMA considerations. Numerical results show the NUMA-optimized hybrid BFS achieves up to 2.2x speedup over the original algorithm.
Graph500 and Green Graph500 benchmarks on SGI UV2000 @ SGI UG SC14Yuichiro Yasui
The document discusses Graph500 and Green Graph500 benchmarks for evaluating graph processing performance on the SGI UV2000 system. It provides an overview of the benchmarks and describes testing various graph workloads, including social networks and road networks, on different hardware from smartphones to supercomputers. The authors aim to optimize breadth-first search (BFS) graph algorithms on the NUMA-based SGI UV2000 without using MPI through NUMA-aware techniques.
NUMA-aware Scalable Graph Traversal on SGI UV SystemsYuichiro Yasui
The document discusses NUMA-aware scalable graph traversal on SGI UV systems. It proposes an efficient NUMA-aware breadth-first search (BFS) algorithm for large-scale graph processing by pruning remote edge traversals. Numerical results on SGI UV 300 systems with 32 sockets show the algorithm achieves 219 billion traversed edges per second (GTEPS), setting a new single-node performance record on the Graph500 benchmark.
What we got from the Predicting Red Hat Business Value competitionUmaporn Kerdsaeng
This slide is to share what I've learned from the kaggle competition. There 3 topics -1) Overview of the competition 2) Introduction to Decision Tree and 3) R package XGboost.
Jonathan Lefman presents his work on Superresolution chemical microscopyJonathan Lefman
This document discusses several microscopy techniques including structured illumination fluorescence microscopy, time-of-flight secondary ion mass spectrometry, coherent anti-Stokes Raman scattering microscopy, photoactivated localization microscopy, stimulated emission depletion microscopy, and 4Pi microscopy. It focuses on describing improvements made to structured illumination fluorescence microscopy including parallel GPU processing to accelerate image analysis and a new automated imaging framework. Time-of-flight secondary ion mass spectrometry imaging is discussed with applications to iterative clustering and classification analysis.
The document discusses various disk scheduling algorithms used by operating systems to optimize disk access time and efficiency. It describes common algorithms like First Come First Serve (FCFS), Shortest Seek Time First (SSTF), SCAN, C-SCAN, LOOK, and C-LOOK. For each algorithm, it provides an example to calculate the total seek length for a sample request queue. It then compares the performance of the different algorithms based on total and average seek lengths. In conclusion, it notes that SCAN and C-SCAN work best under heavy disk loads while SSTF and LOOK are commonly used default algorithms.
Dr. Kashif Rasul from Zalando Research in Berlin held this presentation on "Multi-GPU for Deep Learning" on the COMPUTER SCIENCE, MACHINE LEARNING & STATISTICS MEETUP in the Zalando adtech lab Office in Hamburg on 6th September 2017
This document describes implementing a modified particle filter algorithm for localization in an FPGA. The modified algorithm improves speed and accuracy. It was tested through simulations of global localization, localization and tracking, and kidnapping scenarios. The hardware implementation was 34x faster than software and successfully localized the robot in all experiments, demonstrating the FPGA is capable of running the particle filter in real-time.
NUMA-optimized Parallel Breadth-first Search on Multicore Single-node SystemYuichiro Yasui
The document proposes a NUMA-optimized parallel breadth-first search (BFS) algorithm for multicore systems. It discusses how the hybrid BFS algorithm combines top-down and bottom-up approaches but can result in unnecessary edge traversals. The proposal distributes the graph columns to each NUMA node's local memory and binds threads and data to improve locality. It uses a library called ULIBC to intelligently manage CPU affinity and NUMA considerations. Numerical results show the NUMA-optimized hybrid BFS achieves up to 2.2x speedup over the original algorithm.
Graph500 and Green Graph500 benchmarks on SGI UV2000 @ SGI UG SC14Yuichiro Yasui
The document discusses Graph500 and Green Graph500 benchmarks for evaluating graph processing performance on the SGI UV2000 system. It provides an overview of the benchmarks and describes testing various graph workloads, including social networks and road networks, on different hardware from smartphones to supercomputers. The authors aim to optimize breadth-first search (BFS) graph algorithms on the NUMA-based SGI UV2000 without using MPI through NUMA-aware techniques.
NUMA-aware Scalable Graph Traversal on SGI UV SystemsYuichiro Yasui
The document discusses NUMA-aware scalable graph traversal on SGI UV systems. It proposes an efficient NUMA-aware breadth-first search (BFS) algorithm for large-scale graph processing by pruning remote edge traversals. Numerical results on SGI UV 300 systems with 32 sockets show the algorithm achieves 219 billion traversed edges per second (GTEPS), setting a new single-node performance record on the Graph500 benchmark.
1) The document describes a real-time GPU implementation of visual smoke simulation using the incompressible Navier-Stokes equations.
2) Key steps in the simulation algorithm include adding forces, advecting velocity and scalar fields, solving for pressure, projecting the velocity field, and applying boundary conditions.
3) Volume rendering is achieved by slicing the 3D grid from the viewer's perspective and compositing the slices using the "under" operator, implementing shadows using half-angle slicing.
Fast & Energy-Efficient Breadth-First Search on a Single NUMA SystemYuichiro Yasui
This document summarizes a research paper that proposes a degree-aware breadth-first search (BFS) algorithm to improve the performance and energy efficiency of graph processing on non-uniform memory access (NUMA) systems. The paper introduces related work on BFS optimization. It then analyzes bottlenecks in previous NUMA-optimized BFS algorithms and proposes a degree-aware BFS approach. Experimental results show the proposal achieves faster performance on the Graph500 benchmark and improved energy efficiency on the Green Graph500 benchmark compared to prior work.
Neighbourhood Preserving Quantisation for LSH SIGIR PosterSean Moran
This document proposes a neighbourhood preserving quantisation (NPQ) method for locality sensitive hashing (LSH) that assigns multiple bits per hyperplane using multiple thresholds, rather than the standard single bit. The NPQ method optimizes an F1 score using pairwise constraints from training data to determine threshold values. Evaluation on image retrieval tasks shows NPQ consistently outperforms single and double bit baselines across different projection methods, achieving higher precision-recall curves, especially at higher bit rates. Future work includes exploring variable bits per hyperplane and full retrieval evaluations.
This document discusses advancements in tiled-based compute rendering. It describes current proven tiled rendering techniques used in games. It then discusses opportunities for improvement like using parallel reduction to calculate depth bounds more efficiently than atomics, improved light culling techniques like modified Half-Z, and clustered rendering which divides the screen into tiles and slices to reduce lighting workloads. The document concludes clustered shading has potential savings on culling and offers benefits over traditional 2D tiling.
GDC16: Improving geometry culling for Deus Ex: Mankind Divided by Nicolas TrudelUmbra Software
In this presentation Nicolas Trudel, a Graphics Programmer from Eidos-Montréal describes how they integrated Umbra in their custom made Dawn Engine to improve geometry culling for their latest game. Slides also include a short description of Umbra in general for Sampo Lappalainen, and also a future roadmap from the company's CEO Otso Mäkinen.
LHCb Computing Workshop 2018: PV finding with CNNsHenry Schreiner
The document discusses using a convolutional neural network (CNN) to quickly find primary vertices (PVs) in high-energy physics events recorded by the LHCb experiment. A prototype tracking algorithm is used to generate a 1D kernel density estimate (KDE) histogram from hit triplets. This histogram is then used to train a CNN to predict the locations of PVs. Initial results show the CNN approach can find PVs with 70-75% efficiency and a false positive rate of 0.08-0.13, outperforming current algorithms. Further work aims to improve resolution, find secondary vertices, and integrate the approach into iterative tracking.
This document outlines a proposed VLSI architecture for deformable motion estimation using the Adaptive Rood Pattern Search (ARPS) technique. It begins with an introduction to motion estimation and the ARPS method. It then presents the objectives to design an efficient architecture using ARPS and enhance it for mesh-based motion estimation. Simulation results showing the performance of ARPS are provided, followed by descriptions of the proposed architecture and Xilinx simulation results. Future work plans to optimize the architecture and develop an adaptive mesh-based motion estimation.
1) The document discusses using Scalasca performance analysis tool to profile an application called LSMS running on the ORNL supercomputer.
2) Issues were encountered compiling LSMS with CUDA and OpenMP directives, which were resolved by adding OpenMP header files.
3) Selective instrumentation was used to filter high cost regions and reduce tracing memory requirements for Scalasca.
DynamicFusion is a method for reconstructing and tracking non-rigid scenes in real-time by extending KinectFusion. It uses a volumetric truncated signed distance function (TSDF) to integrate depth maps from multiple viewpoints into a global reconstruction. Live depth frames are aligned to a dense surface prediction generated by raycasting the TSDF. This closes the loop between mapping and localization for tracking dynamic, non-rigid scenes.
BEFLIX is an embedded domain-specific language for generating computer animated films. BEFLIX was created by Ken Knowlton in 1963 for the IBM 7090 mainframe computer with a Stromberg-Carlson SC2040 microfilm recorder for output. Ken Knowlton created BEFLIX while working at Bell Laboratories and used it to make a number of artistic, educational and engineering films.
This document describes a VLSI architecture for block matching motion estimation using the Adaptive Rood Pattern Search (ARPS) algorithm. It aims to enhance the performance of video encoders. The proposed architecture uses ARP and URP modules to perform an initial search and refined search. It consists of address generation, comparison, and sum of absolute difference blocks. Simulation results show the architecture achieves similar PSNR to full search with significantly fewer search points, indicating better computational efficiency.
The document summarizes a student project to develop an unmanned aerial vehicle (UAV) for terrain mapping. The goals were to build a functional UAV that could collect lidar data and video to create digital elevation models. Software included MATLAB and C++ for autonomous flight control. Hardware included a Pixhawk flight controller, GPS, lidar sensor, and other components. Initial simulated flight tests were promising. Future work would include live testing and controller optimization. Students learned lessons about scheduling, equipment choices, and communication.
論文紹介"DynamicFusion: Reconstruction and Tracking of Non-‐rigid Scenes in Real...Ken Sakurada
CVPR2015(Best Paper Award)の論文紹介
"DynamicFusion: Reconstruction and Tracking of Non-‐rigid Scenes in Real-‐Time"
Richard A. Newcombe, Dieter Fox, Steven M. Seitz
内容に関して何かお気づきになりましたら,スライドに記載されているメールアドレスにご連絡頂けると幸いです
This document describes an experiment to verify the laws of conservation of momentum and energy using a track, two trolleys, and two light barriers. Velocities of the trolleys are measured before and after collision using the light barriers. Measured values are transferred to tables to evaluate conservation of momentum, total momentum, energy, total energy, and energy loss. Formulas shown can be used to compare results to theory for elastic and inelastic collisions.
This document summarizes surveying work conducted at the Mudabi site in 2009 and outlines plans for future work. It discusses using a total station, data collector, and software like AutoCAD and ArcGIS to create site maps, excavation grids, topographies, and cross sections. Future possibilities mentioned include photo modeling with photomodeler, point cloud modeling with active laser scanning, and creating 3D models with photosynth. The document provides technical specifications about units, coordinates, and accuracy and offers tips for working in the desert conditions.
The Intersection of Game Engines & GPUs: Current & Future (Graphics Hardware ...Johan Andersson
The document discusses current and future uses of graphics processing units (GPUs) in game engines. It covers topics like shader programming, parallel rendering, texture techniques, raytracing, and general purpose GPU (GPGPU) computing. The author envisions future improvements like more robust shader subroutines, enhanced texture sampling capabilities, hardware-accelerated sparse textures, and limited case raytracing integrated into game engines.
Hashing has witnessed an increase in popularity over the
past few years due to the promise of compact encoding and fast query
time. In order to be effective hashing methods must maximally preserve
the similarity between the data points in the underlying binary representation.
The current best performing hashing techniques have utilised
supervision. In this paper we propose a two-step iterative scheme, Graph
Regularised Hashing (GRH), for incrementally adjusting the positioning
of the hashing hypersurfaces to better conform to the supervisory signal:
in the first step the binary bits are regularised using a data similarity
graph so that similar data points receive similar bits. In the second
step the regularised hashcodes form targets for a set of binary classifiers
which shift the position of each hypersurface so as to separate opposite
bits with maximum margin. GRH exhibits superior retrieval accuracy to
competing hashing methods.
Coq is a proof assistant based on type theory that can be used to formally verify programs and proofs. It supports program extraction to OCaml and can be used to prove properties of programs written in languages like OCaml, Java, C, and Assembly. Coq has been used to verify high assurance systems like the seL4 microkernel and TLS and JavaCard implementations. Formal verification in Coq is based on the Curry-Howard correspondence where types correspond to propositions and programs correspond to proofs. Tactics and rewriting rules are used to interactively prove goals in Coq.
The HDF Group provides software for managing large, complex data and services to support users of this technology. It derives most of its revenue from projects related to earth science, including supporting HDF-EOS, JPSS, and other earth science projects. It maintains various tools for working with HDF files and conducts maintenance, support, and development activities to support new versions and capabilities of HDF libraries and software.
1) The document describes a real-time GPU implementation of visual smoke simulation using the incompressible Navier-Stokes equations.
2) Key steps in the simulation algorithm include adding forces, advecting velocity and scalar fields, solving for pressure, projecting the velocity field, and applying boundary conditions.
3) Volume rendering is achieved by slicing the 3D grid from the viewer's perspective and compositing the slices using the "under" operator, implementing shadows using half-angle slicing.
Fast & Energy-Efficient Breadth-First Search on a Single NUMA SystemYuichiro Yasui
This document summarizes a research paper that proposes a degree-aware breadth-first search (BFS) algorithm to improve the performance and energy efficiency of graph processing on non-uniform memory access (NUMA) systems. The paper introduces related work on BFS optimization. It then analyzes bottlenecks in previous NUMA-optimized BFS algorithms and proposes a degree-aware BFS approach. Experimental results show the proposal achieves faster performance on the Graph500 benchmark and improved energy efficiency on the Green Graph500 benchmark compared to prior work.
Neighbourhood Preserving Quantisation for LSH SIGIR PosterSean Moran
This document proposes a neighbourhood preserving quantisation (NPQ) method for locality sensitive hashing (LSH) that assigns multiple bits per hyperplane using multiple thresholds, rather than the standard single bit. The NPQ method optimizes an F1 score using pairwise constraints from training data to determine threshold values. Evaluation on image retrieval tasks shows NPQ consistently outperforms single and double bit baselines across different projection methods, achieving higher precision-recall curves, especially at higher bit rates. Future work includes exploring variable bits per hyperplane and full retrieval evaluations.
This document discusses advancements in tiled-based compute rendering. It describes current proven tiled rendering techniques used in games. It then discusses opportunities for improvement like using parallel reduction to calculate depth bounds more efficiently than atomics, improved light culling techniques like modified Half-Z, and clustered rendering which divides the screen into tiles and slices to reduce lighting workloads. The document concludes clustered shading has potential savings on culling and offers benefits over traditional 2D tiling.
GDC16: Improving geometry culling for Deus Ex: Mankind Divided by Nicolas TrudelUmbra Software
In this presentation Nicolas Trudel, a Graphics Programmer from Eidos-Montréal describes how they integrated Umbra in their custom made Dawn Engine to improve geometry culling for their latest game. Slides also include a short description of Umbra in general for Sampo Lappalainen, and also a future roadmap from the company's CEO Otso Mäkinen.
LHCb Computing Workshop 2018: PV finding with CNNsHenry Schreiner
The document discusses using a convolutional neural network (CNN) to quickly find primary vertices (PVs) in high-energy physics events recorded by the LHCb experiment. A prototype tracking algorithm is used to generate a 1D kernel density estimate (KDE) histogram from hit triplets. This histogram is then used to train a CNN to predict the locations of PVs. Initial results show the CNN approach can find PVs with 70-75% efficiency and a false positive rate of 0.08-0.13, outperforming current algorithms. Further work aims to improve resolution, find secondary vertices, and integrate the approach into iterative tracking.
This document outlines a proposed VLSI architecture for deformable motion estimation using the Adaptive Rood Pattern Search (ARPS) technique. It begins with an introduction to motion estimation and the ARPS method. It then presents the objectives to design an efficient architecture using ARPS and enhance it for mesh-based motion estimation. Simulation results showing the performance of ARPS are provided, followed by descriptions of the proposed architecture and Xilinx simulation results. Future work plans to optimize the architecture and develop an adaptive mesh-based motion estimation.
1) The document discusses using Scalasca performance analysis tool to profile an application called LSMS running on the ORNL supercomputer.
2) Issues were encountered compiling LSMS with CUDA and OpenMP directives, which were resolved by adding OpenMP header files.
3) Selective instrumentation was used to filter high cost regions and reduce tracing memory requirements for Scalasca.
DynamicFusion is a method for reconstructing and tracking non-rigid scenes in real-time by extending KinectFusion. It uses a volumetric truncated signed distance function (TSDF) to integrate depth maps from multiple viewpoints into a global reconstruction. Live depth frames are aligned to a dense surface prediction generated by raycasting the TSDF. This closes the loop between mapping and localization for tracking dynamic, non-rigid scenes.
BEFLIX is an embedded domain-specific language for generating computer animated films. BEFLIX was created by Ken Knowlton in 1963 for the IBM 7090 mainframe computer with a Stromberg-Carlson SC2040 microfilm recorder for output. Ken Knowlton created BEFLIX while working at Bell Laboratories and used it to make a number of artistic, educational and engineering films.
This document describes a VLSI architecture for block matching motion estimation using the Adaptive Rood Pattern Search (ARPS) algorithm. It aims to enhance the performance of video encoders. The proposed architecture uses ARP and URP modules to perform an initial search and refined search. It consists of address generation, comparison, and sum of absolute difference blocks. Simulation results show the architecture achieves similar PSNR to full search with significantly fewer search points, indicating better computational efficiency.
The document summarizes a student project to develop an unmanned aerial vehicle (UAV) for terrain mapping. The goals were to build a functional UAV that could collect lidar data and video to create digital elevation models. Software included MATLAB and C++ for autonomous flight control. Hardware included a Pixhawk flight controller, GPS, lidar sensor, and other components. Initial simulated flight tests were promising. Future work would include live testing and controller optimization. Students learned lessons about scheduling, equipment choices, and communication.
論文紹介"DynamicFusion: Reconstruction and Tracking of Non-‐rigid Scenes in Real...Ken Sakurada
CVPR2015(Best Paper Award)の論文紹介
"DynamicFusion: Reconstruction and Tracking of Non-‐rigid Scenes in Real-‐Time"
Richard A. Newcombe, Dieter Fox, Steven M. Seitz
内容に関して何かお気づきになりましたら,スライドに記載されているメールアドレスにご連絡頂けると幸いです
This document describes an experiment to verify the laws of conservation of momentum and energy using a track, two trolleys, and two light barriers. Velocities of the trolleys are measured before and after collision using the light barriers. Measured values are transferred to tables to evaluate conservation of momentum, total momentum, energy, total energy, and energy loss. Formulas shown can be used to compare results to theory for elastic and inelastic collisions.
This document summarizes surveying work conducted at the Mudabi site in 2009 and outlines plans for future work. It discusses using a total station, data collector, and software like AutoCAD and ArcGIS to create site maps, excavation grids, topographies, and cross sections. Future possibilities mentioned include photo modeling with photomodeler, point cloud modeling with active laser scanning, and creating 3D models with photosynth. The document provides technical specifications about units, coordinates, and accuracy and offers tips for working in the desert conditions.
The Intersection of Game Engines & GPUs: Current & Future (Graphics Hardware ...Johan Andersson
The document discusses current and future uses of graphics processing units (GPUs) in game engines. It covers topics like shader programming, parallel rendering, texture techniques, raytracing, and general purpose GPU (GPGPU) computing. The author envisions future improvements like more robust shader subroutines, enhanced texture sampling capabilities, hardware-accelerated sparse textures, and limited case raytracing integrated into game engines.
Hashing has witnessed an increase in popularity over the
past few years due to the promise of compact encoding and fast query
time. In order to be effective hashing methods must maximally preserve
the similarity between the data points in the underlying binary representation.
The current best performing hashing techniques have utilised
supervision. In this paper we propose a two-step iterative scheme, Graph
Regularised Hashing (GRH), for incrementally adjusting the positioning
of the hashing hypersurfaces to better conform to the supervisory signal:
in the first step the binary bits are regularised using a data similarity
graph so that similar data points receive similar bits. In the second
step the regularised hashcodes form targets for a set of binary classifiers
which shift the position of each hypersurface so as to separate opposite
bits with maximum margin. GRH exhibits superior retrieval accuracy to
competing hashing methods.
Coq is a proof assistant based on type theory that can be used to formally verify programs and proofs. It supports program extraction to OCaml and can be used to prove properties of programs written in languages like OCaml, Java, C, and Assembly. Coq has been used to verify high assurance systems like the seL4 microkernel and TLS and JavaCard implementations. Formal verification in Coq is based on the Curry-Howard correspondence where types correspond to propositions and programs correspond to proofs. Tactics and rewriting rules are used to interactively prove goals in Coq.
The HDF Group provides software for managing large, complex data and services to support users of this technology. It derives most of its revenue from projects related to earth science, including supporting HDF-EOS, JPSS, and other earth science projects. It maintains various tools for working with HDF files and conducts maintenance, support, and development activities to support new versions and capabilities of HDF libraries and software.
This document describes IBM's Visualization Data Explorer (DX), a data analysis and visualization tool. DX allows users to work with data from multiple sources using a powerful and unified data model. It provides a visual programming environment and large library of modules for importing, analyzing, displaying, and exporting data. Examples of DX use cases are shown from fields like computational fluid dynamics, earth science, and NASA research.
This document discusses the development of HDF Explorer software for visualizing oceanographic model output data. It describes how the developers switched from using proprietary binary formats to the HDF data format for portability and access to graphical tools. It also discusses the HDF Explorer software itself, which was created to provide a graphical interface for visualizing the specific features of their ocean model, including grids, density fields, and velocity fields. The document outlines future plans to utilize HDF-EOS and add additional visualization capabilities like 3D and contours to the HDF Explorer software.
The document describes HDF Server (h5serv), which exposes HDF5 files via a RESTful API. H5serv allows full read/write access and supports HDF5 features like compression and hyperslab selection. It uses the Tornado framework to implement a stateless, cacheable API accessed through HTTP requests in JSON. This provides a web interface for HDF5 data while maintaining HDF5 functionality. Future plans include client libraries, authentication/authorization, and improving performance for large repositories.
The document discusses the HDF-EOS data format and software toolkit. It summarizes recent additions to the toolkit, including new capabilities for handling swath data and accessing metadata. Near-future development plans include additional testing and preparing the software and test data for the EOS-AM1 launch. Potential enhancements discussed include supporting new data types and sensor geometries, incorporating HDF5, and adding more sophisticated subsetting capabilities. Maintenance and user support is provided by ECS through 2022.
The document discusses MrSID, a wavelet-based image compression technology that allows for instant viewing and manipulation of massive raster images locally and over networks while maintaining high image quality. MrSID offers advantages over other formats like seamless mosaicking, multiresolution viewing, and selective decompression that allows viewing parts of large images quickly. Integrating MrSID's technology and file format into NASA's EOSDIS system could allow terabytes of remote sensing data to be accessed more efficiently by scientists, commercial users, and software applications.
The document discusses the benefits of exercise for mental health. Regular physical activity can help reduce anxiety and depression and improve mood and cognitive function. Exercise causes chemical changes in the brain that may help protect against developing mental illness and improve symptoms for those who already suffer from conditions like anxiety and depression.
The document summarizes a prototype for dataset-independent subsetting developed by UAH. The prototype allows users to spatially, temporally, and spectrally subset HDF-EOS format Earth science datasets via a web interface. It extracts only the requested data to reduce delivery time and resource usage. However, its use is currently limited as HDF-EOS has not been widely adopted and many legacy datasets are not in its format.
This document discusses incorporating ISO metadata standards into HDF files using the HDF Product Designer tool. It describes how the HDF Product Designer allows users to import pre-built ISO metadata components from a separate project into their HDF file designs. This allows essential contextual data or metadata to be stored in HDF5 files according to ISO 19115 standards.
The document discusses indexing methods for HDF5 files to enable efficient searching and access of data based on data values. It describes several existing implementations of HDF5 indexing, including PyTables, FastQuery/FastBit, Alacrity, and prototypes from The HDF Group. It also outlines current and future work to develop indexing and querying capabilities within HDF5 to allow complex multi-dimensional searches across metadata and datasets.
This document discusses the development of PyHexad, a Python-based add-in for Excel that allows users to access and analyze HDF5 data directly in Excel. PyHexad 0.1 allows users to display HDF5 file contents, read arrays and tables into Excel, and read HDF5 images. The developer is seeking feedback on usability, the Python dependency, and interest in helping advance the project to version 1.0. A prototype will be released in early August for testing and further input.
This document discusses expert systems and conventions for data modeling. It provides an overview of expert systems and how rule-based systems work using examples like traffic lights and Conway's Game of Life. It describes how an expert system could be used for the HDF Product Designer to enforce data modeling conventions. The status, challenges, and future work are outlined for integrating an expert system into the HDF Product Designer to provide convention knowledge and guide the data modeling process.
HDF is a file format for managing scientific data in heterogeneous environments. It provides data interoperability through I/O software, utilities, and search/access tools. HDF supports a variety of data types and structures, large datasets, metadata, portability across systems, fast I/O, and efficient storage. HDF-EOS extends HDF to define standard profiles for organizing Earth science remote sensing and in-situ data.
The document describes HDF-EOS5, an extension of HDF used by NASA for Earth science data. HDF-EOS5 is based on HDF5 and contains standardized structures for gridded, swath, point, and zonal average data. It provides a library for reading, writing, and manipulating these data structures and their associated metadata. The library contains functions prefixed with "HE5_" for accessing, defining, input/output, inquiry, and subsetting HDF-EOS5 data.
This document provides an overview of HDF-EOS, which is an extension to HDF that defines standard data structures for remote sensing and in-situ data with tightly coupled geolocation information. It describes the core components of HDF-EOS files, including Grid, Swath, and Point structures, and provides examples. It also outlines the development of an HDF5-based version to overcome limitations of the HDF4-based library and allow for larger files.
Deep Learning, Microsoft Cognitive Toolkit (CNTK) and Azure Machine Learning ...Naoki (Neo) SATO
The document provides information about Microsoft's Cognitive Toolkit (CNTK), including benchmark performance comparisons with other deep learning frameworks and examples of using CNTK for common neural network architectures and natural language processing tasks. It shows that CNTK achieves state-of-the-art performance and scales nearly linearly with multiple GPUs. The document also provides code examples for defining common neural network components and training models with CNTK.
The document discusses simultaneous localization and mapping (SLAM) techniques for dense 3D reconstruction of indoor scenes. It presents the deformation graph (D-Graph) approach which can accurately model small-scale environments or estimate trajectories over large-scales. The system takes in RGB-D frame data, extracts point clouds and pose information, builds a truncated signed distance function (TSDF) and pose graph, then optimizes poses and outputs a 3D point cloud map. It compares to other dense visual SLAM algorithms on metrics like trajectory and surface model error.
Here are some useful GDB commands for debugging:
- break <function> - Set a breakpoint at a function
- break <file:line> - Set a breakpoint at a line in a file
- run - Start program execution
- next/n - Step over to next line, stepping over function calls
- step/s - Step into function calls
- finish - Step out of current function
- print/p <variable> - Print value of a variable
- backtrace/bt - Print the call stack
- info breakpoints/ib - List breakpoints
- delete <breakpoint#> - Delete a breakpoint
- layout src - Switch layout to source code view
- layout asm - Switch layout
The document summarizes the use of the Sector and Sphere cloud computing software on the Open Cloud Testbed for the SC08 Bandwidth Challenge. Key points include:
- Sector is a distributed storage system and Sphere simplifies distributed data processing using a map-reduce model.
- The Open Cloud Testbed provided 101 nodes across 4 locations for running applications like TeraSort (sorting 1TB of data) and CreditStone (analyzing 3TB of credit card transactions).
- Sector/Sphere applications achieved transfer rates of up to 20Gbps for TeraSort and 7.2Gbps for CreditStone, utilizing the distributed resources for large-scale data processing.
Your Game Needs Direct3D 11, So Get Started Now!Johan Andersson
Direct3D 11 will have tessellation for smoother curves and finer details. The new compute shader will make postprocessing faster and easier. You'll need Direct3D 11 to have the best graphics, and this talk will show you how you can get started using current generation hardware.
S51281 - Accelerate Data Science in Python with RAPIDS_1679330128290001YmT7.pdfDLow6
RAPIDS accelerates data science and machine learning workflows in Python by leveraging GPUs. It includes cuDF for GPU-accelerated pandas functionality, cuML for scikit-learn compatible machine learning algorithms, cuGraph for graph analytics, and integrations with Dask and Spark. RAPIDS has a large community of contributors and is used by many Fortune 100 companies to speed up workflows, reduce costs, and scale to large datasets.
The document summarizes the key features and capabilities of Direct3D 10, which was designed to maximize GPU performance by reducing CPU overhead and enabling more work to be done on the GPU. Some of the main features discussed include constant buffers, geometry shaders, texture arrays, and other capabilities that reduce draw calls and state changes. Direct3D 10 also provides a standardized, consistent API and enables new visual effects by exposing more of the GPU's programmability and functionality to developers.
Status of HDF-EOS and access tools will be summarized. Updates on HDF-EOS, TOOLKIT, HDFView plug-in and The HDF-EOS to GeoTIFF (HEG) conversion tool, including recent changes to the software, ongoing maintenance, upcoming releases, future plans, and issues will be discussed.
The document discusses using the OGC Web Coverage Service (WCS) protocol to deliver air quality data from various sources through a system called DataFed. The WCS allows querying distributed air quality monitoring data in various formats. It provides a common data model and can deliver gridded data, images, and point data like that from monitoring stations. For air quality analysis, extending WCS to better support point data from stations would be useful.
Achitecture Aware Algorithms and Software for Peta and Exascaleinside-BigData.com
Jack Dongarra from the University of Tennessee presented these slides at Ken Kennedy Institute of Information Technology on Feb 13, 2014.
Listen to the podcast review of this talk: http://insidehpc.com/2014/02/13/week-hpc-jack-dongarra-talks-algorithms-exascale/
RAPIDS – Open GPU-accelerated Data ScienceData Works MD
RAPIDS – Open GPU-accelerated Data Science
RAPIDS is an initiative driven by NVIDIA to accelerate the complete end-to-end data science ecosystem with GPUs. It consists of several open source projects that expose familiar interfaces making it easy to accelerate the entire data science pipeline- from the ETL and data wrangling to feature engineering, statistical modeling, machine learning, and graph analysis.
Corey J. Nolet
Corey has a passion for understanding the world through the analysis of data. He is a developer on the RAPIDS open source project focused on accelerating machine learning algorithms with GPUs.
Adam Thompson
Adam Thompson is a Senior Solutions Architect at NVIDIA. With a background in signal processing, he has spent his career participating in and leading programs focused on deep learning for RF classification, data compression, high-performance computing, and managing and designing applications targeting large collection frameworks. His research interests include deep learning, high-performance computing, systems engineering, cloud architecture/integration, and statistical signal processing. He holds a Masters degree in Electrical & Computer Engineering from Georgia Tech and a Bachelors from Clemson University.
With the open source Geo2tag platform, developers can use JSON or XML to manage location references in apps for Nokia X and Nokia Asha phones. In this webinar, we’ll show how to use the Geo2tag API and how to manage a local database of georeferences. We’ll begin the training by introducing the fundamentals of Location Based Services and the REST API of Geo2Tag LBS Platform (www.geo2tag.org). We’ll focus on networking, JSON and web services. Then we will demonstrate several applications developed on top of Geo2Tagand share the newest enhancements to the platform. We’ll end the training with a discussion of integrating Geo2Tag and third-party map widgets.
State of the Art Web Mapping with Open SourceOSCON Byrum
This document discusses the importance of open source tools and data for web mapping. It begins by providing background on TileMill and Mapbox, which provide open source tools for making maps. It then discusses key concepts in web mapping like geospatial data formats, tile rendering, and minimal code examples. Modern approaches to web mapping involve preprocessing data, using tile renderers and caches, and gradually rendering more client-side. Upcoming improvements may optimize tiled formats and storage. TileMill is demonstrated as an open source tool for making maps. The talk concludes by emphasizing other open mapping tools like CartoDB, Stamen, and CartoDB that build on these concepts.
Klessydra t - designing vector coprocessors for multi-threaded edge-computing...RISC-V International
The document describes a proposed Klessydra-T1 vector coprocessor architecture designed for multi-threaded edge computing cores. It achieves a 3x speedup over a baseline core through configurable SIMD and MIMD vector acceleration schemes. Benchmark results show cycle count reductions for workloads like convolution and matrix multiplication when using the coprocessor in various SISD, SIMD, and MIMD configurations. Resource utilization and maximum frequency are also analyzed.
2006-01-11 Data Flow & Interoperability in DataFed Service-based AQ Analysis ...Rudolf Husar
The document discusses using open standards like OGC Web Coverage Service (WCS) to provide access to air quality data through web services. WCS allows querying subsets of coverages, which are datasets representing varying phenomena over space and time. It is applicable to grid, image and point data types. Efforts are ongoing to add point coverage support for monitoring station data and improve compatibility between WCS servers and clients.
presentation about 2 emerging standards activities that I started and led in MPeG, point cloud compression on a new image and video format, and NBMP for media delivery in 5G networks. Presented at Philips R&D in Eindhoven the Netherlands
This document discusses how to optimize HDF5 files for efficient access in cloud object stores. Key optimizations include using large dataset chunk sizes of 1-4 MiB, consolidating internal file metadata, and minimizing variable-length datatypes. The document recommends creating files with paged aggregation and storing file content information in the user block to enable fast discovery of file contents when stored in object stores.
This document provides an overview of HSDS (Highly Scalable Data Service), which is a REST-based service that allows accessing HDF5 data stored in the cloud. It discusses how HSDS maps HDF5 objects like datasets and groups to individual cloud storage objects to optimize performance. The document also describes how HSDS was used to improve access performance for NASA ICESat-2 HDF5 data on AWS S3 by hyper-chunking datasets into larger chunks spanning multiple original HDF5 chunks. Benchmark results showed that accessing the data through HSDS provided over 2x faster performance than other methods like ROS3 or S3FS that directly access the cloud storage.
This document summarizes the current status and focus of the HDF Group. It discusses that the HDF Group is located in Champaign, IL and is a non-profit organization focused on developing and maintaining HDF software and data formats. It provides an overview of recent HDF5, HDF4 and HDFView releases and notes areas of focus for software quality improvements, increased transparency, strengthening the community, and modernizing HDF products. It invites support and participation in upcoming user group meetings.
This document provides an overview of HSDS (HDF Server and Data Service), which allows HDF5 files to be stored and accessed from the cloud. Key points include:
- HSDS maps HDF5 objects like datasets and groups to individual cloud storage objects for scalability and parallelism.
- Features include streaming support, fancy indexing for complex queries, and caching for improved performance.
- HSDS can be deployed on Docker, Kubernetes, or AWS Lambda depending on needs.
- Case studies show HSDS is used by organizations like NREL and NSF to make petabytes of scientific data publicly accessible in the cloud.
This document discusses creating cloud-optimized HDF5 files by rearranging internal structures for more efficient data access in cloud object stores. It describes cloud-native and cloud-optimized storage formats, with the latter involving storing the entire HDF5 file as a single object. The benefits of cloud-optimized HDF5 include fast scanning and using the HDF5 library. Key aspects covered include using optimal chunk sizes, compression, and minimizing variable-length datatypes.
This document discusses updates and performance improvements to the HDF5 OPeNDAP data handler. It provides a history of the handler since 2001 and describes recent updates including supporting DAP4, new data types, and NetCDF data models. A performance study showed that passing compressed HDF5 data through the handler without decompressing/recompressing led to speedups of around 17-30x by leveraging HDF5 direct I/O APIs. This allows outputting HDF5 files as NetCDF files much faster through the handler.
This document provides instructions for using the Hyrax software to serve scientific data files stored on Amazon S3 using the OPeNDAP data access protocol. It describes how to generate ancillary metadata files called DMR++ files using the get_dmrpp tool that provide information about the data file structure and locations. The document explains how to run get_dmrpp inside a Docker container to process data files on S3 and generate customized DMR++ files that the Hyrax server can use to serve the files to clients.
This document provides an overview and examples of accessing cloud data and services using the Earthdata Login (EDL), Pydap, and MATLAB. It discusses some common problems users encounter, such as being unable to access HDF5 data on AWS S3 using MATLAB or read data from OPeNDAP servers using Pydap. Solutions presented include using EDL to get temporary AWS tokens for S3 access in MATLAB and providing code examples on the HDFEOS website to help users access S3 data and OPeNDAP services. The document also notes some limitations, such as tokens being valid for only 1 hour, and workarounds like requesting new tokens or using the MATLAB HDF5 API instead of the netCDF API.
The HDF5 Roadmap and New Features document outlines upcoming changes and improvements to the HDF5 library. Key points include:
- HDF5 1.13.x releases will include new features like selection I/O, the Onion VFD for versioned files, improved VFD SWMR for single-writer multiple-reader access, and subfiling for parallel I/O.
- The Virtual Object Layer allows customizing HDF5 object storage and introduces terminal and pass-through connectors.
- The Onion VFD stores versions of HDF5 files in a separate onion file for versioned access.
- VFD SWMR improves on legacy SWMR by implementing single-writer multiple-reader capabilities
This document discusses user analysis of the HDFEOS.org website and plans for future improvements. It finds that the majority of the site's 100 daily users are "quiet", not posting on forums or other interactive elements. The main user types are locators, who search for examples or data; mergers, who combine or mosaic datasets; and converters, who change file formats. The document outlines recent updates focused on these user types, like adding Python examples for subsetting and calculating latitude and longitude. It proposes future work on artificial intelligence/machine learning uses of HDF files and examples for processing HDF data in the cloud.
This document summarizes a presentation about the current status and future directions of the Hierarchical Data Format (HDF) software. It provides updates on recent HDF5 releases, development efforts including new compression methods and ways to access HDF5 data, and outreach resources. It concludes by inviting the audience to share wishes for future HDF development.
The document describes H5Coro, a new C++ library for reading HDF5 files from cloud storage. H5Coro was created to optimize HDF5 reading for cloud environments by minimizing I/O operations through caching and efficient HTTP requests. Performance tests showed H5Coro was 77-132x faster than the previous HDF5 library at reading HDF5 data from Amazon S3 for NASA's SlideRule project. H5Coro supports common HDF5 elements but does not support writing or some complex HDF5 data types and messages to focus on optimized read-only performance for time series data stored sequentially in memory.
This document summarizes MathWorks' work to modernize MATLAB's support for HDF5. Key points include:
1) MATLAB now supports HDF5 1.10.7 features like single-writer/multiple-reader access and virtual datasets through new and updated low-level functions.
2) Performance benchmarks show some improvements but also regressions compared to the previous HDF5 version, and work continues to optimize code and support future versions.
3) There are compatibility considerations for Linux filter plugins, but interim solutions are provided until MathWorks can ship a single HDF5 version.
HSDS provides HDF as a service through a REST API that can scale across nodes. New releases will enable serverless operation using AWS Lambda or direct client access without a server. This allows HDF data to be accessed remotely without managing servers. HSDS stores each HDF object separately, making it compatible with cloud object storage. Performance on AWS Lambda is slower than a dedicated server but has no management overhead. Direct client access has better performance but limits collaboration between clients.
HDF5 and Zarr are data formats that can be used to store and access scientific data. This presentation discusses approaches to translating between the two formats. It describes how HDF5 files were translated to the Zarr format by creating a separate Zarr store to hold HDF5 file chunks, and storing chunk location metadata. It also discusses an implementation that translates Zarr data to the HDF5 format by using a special chunking layout and storing chunk information in an HDF5 compound dataset. Limitations of the translations include lack of support for some HDF5 dataset properties in Zarr, and lack of support for some Zarr compression methods in the HDF5 implementation.
The document discusses HDF for the cloud, including new features of the HDF Server and what's next. Key points:
- HDF Server uses a "sharded schema" that maps HDF5 objects to individual storage objects, allowing parallel access and updates without transferring entire files.
- Implementations include HSDS software that uses the sharded schema with an API and SDKs for different languages like h5pyd for Python.
- New features of HSDS 0.6 include support for POSIX, Azure, AWS Lambda, and role-based access control.
- Future work includes direct access to storage without a server intermediary for some use cases.
This document compares different methods for accessing HDF and netCDF files stored on Amazon S3, including Apache Drill, THREDDS Data Server (TDS), and HDF5 Virtual File Driver (VFD). A benchmark test of accessing a 24GB HDF5/netCDF-4 file on S3 from Amazon EC2 found that TDS performed the best, responding within 2 minutes, while Apache Drill failed after 7 minutes. The document concludes that TDS 5.0 is the clear winner based on performance and support for role-based access control and HDF4 files, but the best solution depends on use case and software.
This document discusses STARE-PODS, a proposal to NASA/ACCESS-19 to develop a scalable data store for earth science data using the SpatioTemporal Adaptive Resolution Encoding (STARE) indexing scheme. STARE allows diverse earth science data to be unified and indexed, enabling the data to be partitioned and stored in a Parallel Optimized Data Store (PODS) for efficient analysis. The HDF Virtual Object Layer and Virtual Data Set technologies can then provide interfaces to access the data in STARE-PODS in a familiar way. The goal is for STARE-PODS to organize diverse data for alignment and parallel/distributed storage and processing to enable integrative analysis at scale.
This document provides an overview and update on HDF5 and its ecosystem. Key points include:
- HDF5 1.12.0 was recently released with new features like the Virtual Object Layer and external references.
- The HDF5 library now supports accessing data in the cloud using connectors like S3 VFD and REST VOL without needing to modify applications.
- Projects like HDFql and H5CPP provide additional interfaces for querying and working with HDF5 files from languages like SQL, C++, and Python.
- The HDF5 community is moving development to GitHub and improving documentation resources on the HDF wiki site.
This document summarizes new features in HDF5 1.12.0, including support for storing references to objects and attributes across files, new storage backends using a virtual object layer (VOL), and virtual file drivers (VFDs) for Amazon S3 and HDFS. It outlines the HDF5 roadmap for 2019-2022, which includes continued support for HDF5 1.8 and 1.10, and new features in future 1.12.x releases like querying, indexing, and provenance tracking.
More from The HDF-EOS Tools and Information Center (20)
AI 101: An Introduction to the Basics and Impact of Artificial IntelligenceIndexBug
Imagine a world where machines not only perform tasks but also learn, adapt, and make decisions. This is the promise of Artificial Intelligence (AI), a technology that's not just enhancing our lives but revolutionizing entire industries.
HCL Notes and Domino License Cost Reduction in the World of DLAUpanagenda
Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-and-domino-license-cost-reduction-in-the-world-of-dlau/
The introduction of DLAU and the CCB & CCX licensing model caused quite a stir in the HCL community. As a Notes and Domino customer, you may have faced challenges with unexpected user counts and license costs. You probably have questions on how this new licensing approach works and how to benefit from it. Most importantly, you likely have budget constraints and want to save money where possible. Don’t worry, we can help with all of this!
We’ll show you how to fix common misconfigurations that cause higher-than-expected user counts, and how to identify accounts which you can deactivate to save money. There are also frequent patterns that can cause unnecessary cost, like using a person document instead of a mail-in for shared mailboxes. We’ll provide examples and solutions for those as well. And naturally we’ll explain the new licensing model.
Join HCL Ambassador Marc Thomas in this webinar with a special guest appearance from Franz Walder. It will give you the tools and know-how to stay on top of what is going on with Domino licensing. You will be able lower your cost through an optimized configuration and keep it low going forward.
These topics will be covered
- Reducing license cost by finding and fixing misconfigurations and superfluous accounts
- How do CCB and CCX licenses really work?
- Understanding the DLAU tool and how to best utilize it
- Tips for common problem areas, like team mailboxes, functional/test users, etc
- Practical examples and best practices to implement right away
Digital Marketing Trends in 2024 | Guide for Staying AheadWask
https://www.wask.co/ebooks/digital-marketing-trends-in-2024
Feeling lost in the digital marketing whirlwind of 2024? Technology is changing, consumer habits are evolving, and staying ahead of the curve feels like a never-ending pursuit. This e-book is your compass. Dive into actionable insights to handle the complexities of modern marketing. From hyper-personalization to the power of user-generated content, learn how to build long-term relationships with your audience and unlock the secrets to success in the ever-shifting digital landscape.
Main news related to the CCS TSI 2023 (2023/1695)Jakub Marek
An English 🇬🇧 translation of a presentation to the speech I gave about the main changes brought by CCS TSI 2023 at the biggest Czech conference on Communications and signalling systems on Railways, which was held in Clarion Hotel Olomouc from 7th to 9th November 2023 (konferenceszt.cz). Attended by around 500 participants and 200 on-line followers.
The original Czech 🇨🇿 version of the presentation can be found here: https://www.slideshare.net/slideshow/hlavni-novinky-souvisejici-s-ccs-tsi-2023-2023-1695/269688092 .
The videorecording (in Czech) from the presentation is available here: https://youtu.be/WzjJWm4IyPk?si=SImb06tuXGb30BEH .
Your One-Stop Shop for Python Success: Top 10 US Python Development Providersakankshawande
Simplify your search for a reliable Python development partner! This list presents the top 10 trusted US providers offering comprehensive Python development services, ensuring your project's success from conception to completion.
Monitoring and Managing Anomaly Detection on OpenShift.pdfTosin Akinosho
Monitoring and Managing Anomaly Detection on OpenShift
Overview
Dive into the world of anomaly detection on edge devices with our comprehensive hands-on tutorial. This SlideShare presentation will guide you through the entire process, from data collection and model training to edge deployment and real-time monitoring. Perfect for those looking to implement robust anomaly detection systems on resource-constrained IoT/edge devices.
Key Topics Covered
1. Introduction to Anomaly Detection
- Understand the fundamentals of anomaly detection and its importance in identifying unusual behavior or failures in systems.
2. Understanding Edge (IoT)
- Learn about edge computing and IoT, and how they enable real-time data processing and decision-making at the source.
3. What is ArgoCD?
- Discover ArgoCD, a declarative, GitOps continuous delivery tool for Kubernetes, and its role in deploying applications on edge devices.
4. Deployment Using ArgoCD for Edge Devices
- Step-by-step guide on deploying anomaly detection models on edge devices using ArgoCD.
5. Introduction to Apache Kafka and S3
- Explore Apache Kafka for real-time data streaming and Amazon S3 for scalable storage solutions.
6. Viewing Kafka Messages in the Data Lake
- Learn how to view and analyze Kafka messages stored in a data lake for better insights.
7. What is Prometheus?
- Get to know Prometheus, an open-source monitoring and alerting toolkit, and its application in monitoring edge devices.
8. Monitoring Application Metrics with Prometheus
- Detailed instructions on setting up Prometheus to monitor the performance and health of your anomaly detection system.
9. What is Camel K?
- Introduction to Camel K, a lightweight integration framework built on Apache Camel, designed for Kubernetes.
10. Configuring Camel K Integrations for Data Pipelines
- Learn how to configure Camel K for seamless data pipeline integrations in your anomaly detection workflow.
11. What is a Jupyter Notebook?
- Overview of Jupyter Notebooks, an open-source web application for creating and sharing documents with live code, equations, visualizations, and narrative text.
12. Jupyter Notebooks with Code Examples
- Hands-on examples and code snippets in Jupyter Notebooks to help you implement and test anomaly detection models.
In the rapidly evolving landscape of technologies, XML continues to play a vital role in structuring, storing, and transporting data across diverse systems. The recent advancements in artificial intelligence (AI) present new methodologies for enhancing XML development workflows, introducing efficiency, automation, and intelligent capabilities. This presentation will outline the scope and perspective of utilizing AI in XML development. The potential benefits and the possible pitfalls will be highlighted, providing a balanced view of the subject.
We will explore the capabilities of AI in understanding XML markup languages and autonomously creating structured XML content. Additionally, we will examine the capacity of AI to enrich plain text with appropriate XML markup. Practical examples and methodological guidelines will be provided to elucidate how AI can be effectively prompted to interpret and generate accurate XML markup.
Further emphasis will be placed on the role of AI in developing XSLT, or schemas such as XSD and Schematron. We will address the techniques and strategies adopted to create prompts for generating code, explaining code, or refactoring the code, and the results achieved.
The discussion will extend to how AI can be used to transform XML content. In particular, the focus will be on the use of AI XPath extension functions in XSLT, Schematron, Schematron Quick Fixes, or for XML content refactoring.
The presentation aims to deliver a comprehensive overview of AI usage in XML development, providing attendees with the necessary knowledge to make informed decisions. Whether you’re at the early stages of adopting AI or considering integrating it in advanced XML development, this presentation will cover all levels of expertise.
By highlighting the potential advantages and challenges of integrating AI with XML development tools and languages, the presentation seeks to inspire thoughtful conversation around the future of XML development. We’ll not only delve into the technical aspects of AI-powered XML development but also discuss practical implications and possible future directions.
Webinar: Designing a schema for a Data WarehouseFederico Razzoli
Are you new to data warehouses (DWH)? Do you need to check whether your data warehouse follows the best practices for a good design? In both cases, this webinar is for you.
A data warehouse is a central relational database that contains all measurements about a business or an organisation. This data comes from a variety of heterogeneous data sources, which includes databases of any type that back the applications used by the company, data files exported by some applications, or APIs provided by internal or external services.
But designing a data warehouse correctly is a hard task, which requires gathering information about the business processes that need to be analysed in the first place. These processes must be translated into so-called star schemas, which means, denormalised databases where each table represents a dimension or facts.
We will discuss these topics:
- How to gather information about a business;
- Understanding dictionaries and how to identify business entities;
- Dimensions and facts;
- Setting a table granularity;
- Types of facts;
- Types of dimensions;
- Snowflakes and how to avoid them;
- Expanding existing dimensions and facts.
How to Interpret Trends in the Kalyan Rajdhani Mix Chart.pdfChart Kalyan
A Mix Chart displays historical data of numbers in a graphical or tabular form. The Kalyan Rajdhani Mix Chart specifically shows the results of a sequence of numbers over different periods.
Ocean lotus Threat actors project by John Sitima 2024 (1).pptxSitimaJohn
Ocean Lotus cyber threat actors represent a sophisticated, persistent, and politically motivated group that poses a significant risk to organizations and individuals in the Southeast Asian region. Their continuous evolution and adaptability underscore the need for robust cybersecurity measures and international cooperation to identify and mitigate the threats posed by such advanced persistent threat groups.
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAUpanagenda
Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-und-domino-lizenzkostenreduzierung-in-der-welt-von-dlau/
DLAU und die Lizenzen nach dem CCB- und CCX-Modell sind für viele in der HCL-Community seit letztem Jahr ein heißes Thema. Als Notes- oder Domino-Kunde haben Sie vielleicht mit unerwartet hohen Benutzerzahlen und Lizenzgebühren zu kämpfen. Sie fragen sich vielleicht, wie diese neue Art der Lizenzierung funktioniert und welchen Nutzen sie Ihnen bringt. Vor allem wollen Sie sicherlich Ihr Budget einhalten und Kosten sparen, wo immer möglich. Das verstehen wir und wir möchten Ihnen dabei helfen!
Wir erklären Ihnen, wie Sie häufige Konfigurationsprobleme lösen können, die dazu führen können, dass mehr Benutzer gezählt werden als nötig, und wie Sie überflüssige oder ungenutzte Konten identifizieren und entfernen können, um Geld zu sparen. Es gibt auch einige Ansätze, die zu unnötigen Ausgaben führen können, z. B. wenn ein Personendokument anstelle eines Mail-Ins für geteilte Mailboxen verwendet wird. Wir zeigen Ihnen solche Fälle und deren Lösungen. Und natürlich erklären wir Ihnen das neue Lizenzmodell.
Nehmen Sie an diesem Webinar teil, bei dem HCL-Ambassador Marc Thomas und Gastredner Franz Walder Ihnen diese neue Welt näherbringen. Es vermittelt Ihnen die Tools und das Know-how, um den Überblick zu bewahren. Sie werden in der Lage sein, Ihre Kosten durch eine optimierte Domino-Konfiguration zu reduzieren und auch in Zukunft gering zu halten.
Diese Themen werden behandelt
- Reduzierung der Lizenzkosten durch Auffinden und Beheben von Fehlkonfigurationen und überflüssigen Konten
- Wie funktionieren CCB- und CCX-Lizenzen wirklich?
- Verstehen des DLAU-Tools und wie man es am besten nutzt
- Tipps für häufige Problembereiche, wie z. B. Team-Postfächer, Funktions-/Testbenutzer usw.
- Praxisbeispiele und Best Practices zum sofortigen Umsetzen
Threats to mobile devices are more prevalent and increasing in scope and complexity. Users of mobile devices desire to take full advantage of the features
available on those devices, but many of the features provide convenience and capability but sacrifice security. This best practices guide outlines steps the users can take to better protect personal devices and information.
Ivanti’s Patch Tuesday breakdown goes beyond patching your applications and brings you the intelligence and guidance needed to prioritize where to focus your attention first. Catch early analysis on our Ivanti blog, then join industry expert Chris Goettl for the Patch Tuesday Webinar Event. There we’ll do a deep dive into each of the bulletins and give guidance on the risks associated with the newly-identified vulnerabilities.
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2024/06/building-and-scaling-ai-applications-with-the-nx-ai-manager-a-presentation-from-network-optix/
Robin van Emden, Senior Director of Data Science at Network Optix, presents the “Building and Scaling AI Applications with the Nx AI Manager,” tutorial at the May 2024 Embedded Vision Summit.
In this presentation, van Emden covers the basics of scaling edge AI solutions using the Nx tool kit. He emphasizes the process of developing AI models and deploying them globally. He also showcases the conversion of AI models and the creation of effective edge AI pipelines, with a focus on pre-processing, model conversion, selecting the appropriate inference engine for the target hardware and post-processing.
van Emden shows how Nx can simplify the developer’s life and facilitate a rapid transition from concept to production-ready applications.He provides valuable insights into developing scalable and efficient edge AI solutions, with a strong focus on practical implementation.
5th LF Energy Power Grid Model Meet-up SlidesDanBrown980551
5th Power Grid Model Meet-up
It is with great pleasure that we extend to you an invitation to the 5th Power Grid Model Meet-up, scheduled for 6th June 2024. This event will adopt a hybrid format, allowing participants to join us either through an online Mircosoft Teams session or in person at TU/e located at Den Dolech 2, Eindhoven, Netherlands. The meet-up will be hosted by Eindhoven University of Technology (TU/e), a research university specializing in engineering science & technology.
Power Grid Model
The global energy transition is placing new and unprecedented demands on Distribution System Operators (DSOs). Alongside upgrades to grid capacity, processes such as digitization, capacity optimization, and congestion management are becoming vital for delivering reliable services.
Power Grid Model is an open source project from Linux Foundation Energy and provides a calculation engine that is increasingly essential for DSOs. It offers a standards-based foundation enabling real-time power systems analysis, simulations of electrical power grids, and sophisticated what-if analysis. In addition, it enables in-depth studies and analysis of the electrical power grid’s behavior and performance. This comprehensive model incorporates essential factors such as power generation capacity, electrical losses, voltage levels, power flows, and system stability.
Power Grid Model is currently being applied in a wide variety of use cases, including grid planning, expansion, reliability, and congestion studies. It can also help in analyzing the impact of renewable energy integration, assessing the effects of disturbances or faults, and developing strategies for grid control and optimization.
What to expect
For the upcoming meetup we are organizing, we have an exciting lineup of activities planned:
-Insightful presentations covering two practical applications of the Power Grid Model.
-An update on the latest advancements in Power Grid -Model technology during the first and second quarters of 2024.
-An interactive brainstorming session to discuss and propose new feature requests.
-An opportunity to connect with fellow Power Grid Model enthusiasts and users.
Driving Business Innovation: Latest Generative AI Advancements & Success StorySafe Software
Are you ready to revolutionize how you handle data? Join us for a webinar where we’ll bring you up to speed with the latest advancements in Generative AI technology and discover how leveraging FME with tools from giants like Google Gemini, Amazon, and Microsoft OpenAI can supercharge your workflow efficiency.
During the hour, we’ll take you through:
Guest Speaker Segment with Hannah Barrington: Dive into the world of dynamic real estate marketing with Hannah, the Marketing Manager at Workspace Group. Hear firsthand how their team generates engaging descriptions for thousands of office units by integrating diverse data sources—from PDF floorplans to web pages—using FME transformers, like OpenAIVisionConnector and AnthropicVisionConnector. This use case will show you how GenAI can streamline content creation for marketing across the board.
Ollama Use Case: Learn how Scenario Specialist Dmitri Bagh has utilized Ollama within FME to input data, create custom models, and enhance security protocols. This segment will include demos to illustrate the full capabilities of FME in AI-driven processes.
Custom AI Models: Discover how to leverage FME to build personalized AI models using your data. Whether it’s populating a model with local data for added security or integrating public AI tools, find out how FME facilitates a versatile and secure approach to AI.
We’ll wrap up with a live Q&A session where you can engage with our experts on your specific use cases, and learn more about optimizing your data workflows with AI.
This webinar is ideal for professionals seeking to harness the power of AI within their data management systems while ensuring high levels of customization and security. Whether you're a novice or an expert, gain actionable insights and strategies to elevate your data processes. Join us to see how FME and AI can revolutionize how you work with data!
3. What is HDF-EOS?
An HDF “Profile”
An extension to HDF
A library built “on top” of HDF
Three new data objects
Three new programming interfaces
3
4. Why HDF-EOS?
Standard HDF lacks well defined ways of
handling some key needs of EOSDIS
Data structures for Earth remote
sensing data and in-situ measurements
with:
– tightly coupled geolocation information
– subsetting services based on geolocation
ECS metadata model
4
5. HDF-EOS Platforms
HDF-EOS Version 2.3 is available for:
Sun SPARC - Solaris
SGI - IRIX
DEC Alpha - Digital UNIX
HP 9000 - HP-UX
IBM RS/6000 - AIX
PC - Windows 95/NT
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6. HDF-EOS Interfaces
C and FORTRAN Interfaces for:
Grid Data (GD)
Point Data (PT)
Swath Data (SW)
6
11. Components of the Grid
Interface
Access
Definition
Basic I/O
Inquiry
Subset
Tiling
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12. Tips on Writing a Grid
Order of calls is significant:
– Setting a compression method affects all
subsequently defined fields
– Setting a tiling scheme affects all
subsequently defined fields
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13. Grid Subsetting Features
By Geolocation
– GDdefboxregion/Gdextractboxregion
By “Vertical” Field
– GDdefvrtregion/GDextractvrtregion
By Time (special case of vertical)
Tip: use Geolocation, then Vertical/
Temporal
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18. Tips on Writing a Point
Every level in a Point data set must be
linked into the hierarchy.
Before two levels can be linked, a link
field must exist.
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19. Point Subsetting Features
By Time
– PTdeftimeperiod/PTextractperiod
By Geolocation
– PTdefboxregion/PTextractregion
Tip: use one or the other, not both
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21. Tips for HDF-EOS Coding
Most operations (read, write, subset)
work on a single field at a time.
Region IDs and Period IDs are interchangeable and can be reused to
further reduce a subset.
Partial writes (appending) on
compressed fields are only supported
through tiling.
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