In this deck from the 2018 Swiss HPC Conference, Axel Koehler from NVIDIA presents: The Convergence of HPC and Deep Learning.
"The intersection of AI and HPC is extending the reach of science and accelerating the pace of scientific innovation like never before. The technology originally developed for HPC has enabled deep learning, and deep learning is enabling many usages in science. Deep learning is also helping deliver real-time results with models that used to take days or months to simulate. The presentation will give an overview about the latest hard- and software developments for HPC and Deep Learning from NVIDIA and will show some examples that Deep Learning can be combined with traditional large scale simulations."
Watch the video: https://wp.me/p3RLHQ-ijM
Learn more: http://nvidia.com
and
http://www.hpcadvisorycouncil.com/events/2018/swiss-workshop/agenda.php
Sign up for our insideHPC Newsletter: http://insidehpc.com/newsletter
In this deck from the 2018 Swiss HPC Conference, Axel Koehler from NVIDIA presents: The Convergence of HPC and Deep Learning.
"The intersection of AI and HPC is extending the reach of science and accelerating the pace of scientific innovation like never before. The technology originally developed for HPC has enabled deep learning, and deep learning is enabling many usages in science. Deep learning is also helping deliver real-time results with models that used to take days or months to simulate. The presentation will give an overview about the latest hard- and software developments for HPC and Deep Learning from NVIDIA and will show some examples that Deep Learning can be combined with traditional large scale simulations."
Watch the video: https://wp.me/p3RLHQ-ijM
Learn more: http://nvidia.com
and
http://www.hpcadvisorycouncil.com/events/2018/swiss-workshop/agenda.php
Sign up for our insideHPC Newsletter: http://insidehpc.com/newsletter
Have you heard that all in-memory databases are equally fast but unreliable, inconsistent and expensive? This session highlights in-memory technology that busts all those myths.
Redis, the fastest database on the planet, is not a simply in-memory key-value data-store; but rather a rich in-memory data-structure engine that serves the world’s most popular apps. Redis Labs’ unique clustering technology enables Redis to be highly reliable, keeping every data byte intact despite hundreds of cloud instance failures and dozens of complete data-center outages. It delivers full CP system characteristics at high performance. And with the latest Redis on Flash technology, Redis Labs achieves close to in-memory performance at 70% lower operational costs. Learn about the best uses of in-memory computing to accelerate everyday applications such as high volume transactions, real time analytics, IoT data ingestion and more.
For the full video of this presentation, please visit:
http://www.embedded-vision.com/platinum-members/embedded-vision-alliance/embedded-vision-training/videos/pages/sept-2016-member-meeting-mit
For more information about embedded vision, please visit:
http://www.embedded-vision.com
Vivienne Sze, Assistant Professor at MIT, delivers the presentation "Energy-efficient Hardware for Embedded Vision and Deep Convolutional Neural Networks" at the September 2016 Embedded Vision Alliance Member Meeting. Sze describes the results of her team's recent research on optimized hardware for deep learning.
Get Your Head in the Cloud - Lessons in GPU Computing with Schlumbergerinside-BigData.com
In this presentation from the GPU Technology Conference, Wyatt Gorman from Google and Abhishek Gupta from Schlumberger present: Get Your Head in the Cloud - Lessons in GPU Computing with Schlumberger.
"Demand for GPUs in High Performance Computing is only growing, and it is costly and difficult to keep pace in an entirely on-premise environment. We will hear from Schlumberger on why and how they are utilizing cloud-based GPU-enabled computing resources from Google Cloud to supply their users with the computing power they need, from exploration and modeling to visualization."
Watch the video: https://wp.me/p3RLHQ-kcl
Learn more: https://www.blog.google/products/google-cloud/schlumberger-chooses-gcp-to-deliver-new-oil-and-gas-technology-platform/
and
https://www.nvidia.com/en-us/gtc/
Optimize Single Particle Orbital (SPO) Evaluations Based on B-splinesIntel® Software
Orbital representations that are based on B-splines are widely used in quantum Monte Carlo (QMC) simulations of solids, which historically take as much as 50 percent of the total runtime. Random access to a large four-dimensional array make it challenging to efficiently use caches and wide vector units in modern CPUs. So, we present node-level optimizations of B-spline evaluations on multicore and manycore shared memory processors.
To increase single instruction multiple data (SIMD) efficiency and bandwidth utilization, we first apply data layout transformation from an array of structures (AoS) to a structure of arrays (SoA). Then, by blocking SoA objects, we optimize cache reuse and get sustained throughput for a range of problem sizes. We implement efficient nested threading in B-spline orbital evaluation kernels, paving the way towards enabling strong scaling of QMC simulations, resulting with performance enhancements. Finally, we employ roofline performance analysis to model the impacts of our optimizations.
The MEW Workshop is now established as a leading national event dedicated to distributed high performance scientific computing. The principle objective is to encourage close contact between the research communities from the Mathematics, Chemistry, Physics and Materials Programmes of EPSRC and the major vendors.
In this deck from Switzerland HPC Conference, Gunter Roeth from NVIDIA presents: Deep Learning on the SaturnV Cluster.
"Machine Learning is among the most important developments in the history of computing. Deep learning is one of the fastest growing areas of machine learning and a hot topic in both academia and industry. It has dramatically improved the state-of-the-art in areas such as speech recognition, computer vision, predicting the activity of drug molecules, and many other machine learning tasks. The basic idea of deep learning is to automatically learn to represent data in multiple layers of increasing abstraction, thus helping to discover intricate structure in large datasets. NVIDIA has invested in SaturnV, a large GPU-accelerated cluster, (#28 on the November 2016 Top500 list) to support internal machine learning projects. After an introduction to deep learning on GPUs, we will address a selection of open questions programmers and users may face when using deep learning for their work on these clusters."
Watch the video: http://wp.me/p3RLHQ-gDv
Learn more: http://www.nvidia.com/object/dgx-saturnv.html
and
http://hpcadvisorycouncil.com/events/2017/swiss-workshop/agenda.php
Sign up for our insideHPC Newsletter: http://insidehpc.com/newsletter
Microsoft Project Olympus AI Accelerator Chassis (HGX-1)inside-BigData.com
In this video from the Open Compute Summit, Siamak Tavallaei from Microsoft presents an overview of the Microsoft Project Olympus AI Accelerator Chassis, also known as the HGX-1.
Watch the presentation video: http://wp.me/p3RLHQ-guX
Sign up for our insideHPC Newsletter: http://insidehpc.com/newsletter
In this deck from the Switzerland HPC Conference, Francis Lam from Huawei presents: A Fresh Look at HPC from Huawei Enterprise.
"High performance computing is rapidly finding new uses in many applications and businesses, enabling the creation of disruptive products and services. Huawei, a global leader in information and communication technologies, brings a broad spectrum of innovative solutions to HPC. This talk examines Huawei's world class HPC solutions and explores creative new ways to solve HPC problems."
Watch the video: http://wp.me/p3RLHQ-gCV
Learn more: http://e.huawei.com/en/solutions/business-needs/data-center/high-performance-computing
and
http://www.hpcadvisorycouncil.com/events/2017/swiss-workshop/agenda.php
Sign up for our insideHPC Newsletter: http://insidehpc.com/newsletter
dCUDA: Distributed GPU Computing with Hardware Overlapinside-BigData.com
Torsten Hoefler from ETH Zurich presented this deck at the Switzerland HPC Conference.
"Over the last decade, CUDA and the underlying GPU hardware architecture have continuously gained popularity in various high-performance computing application domains such as climate modeling, computational chemistry, or machine learning. Despite this popularity, we lack a single coherent programming model for GPU clusters. We therefore introduce the dCUDA programming model, which implements device-side remote memory access with target notification. To hide instruction pipeline latencies, CUDA programs over-decompose the problem and over-subscribe the device by running many more threads than there are hardware execution units. Whenever a thread stalls, the hardware scheduler immediately proceeds with the execution of another thread ready for execution. This latency-hiding technique is key to make best use of the available hardware resources. With dCUDA, we apply latency hiding at cluster scale to automatically overlap computation and communication. Our benchmarks demonstrate perfect overlap for memory bandwidth-bound tasks and good overlap for compute-bound tasks."
Watch the video presentation: http://wp.me/p3RLHQ-gCB
In this deck, Gilad Shainer from Mellanox announces the world’s first HDR 200Gb/s data center interconnect solutions. "These 200Gb/s HDR InfiniBand solutions maintain Mellanox’s generation-ahead leadership while enabling customers and users to leverage an open, standards-based technology that maximizes application performance and scalability while minimizing overall data center total cost of ownership. Mellanox 200Gb/s HDR solutions will become generally available in 2017.
Watch the video presentation: http://insidehpc.com/2016/11/hdr-infiniband/
High-Performance and Scalable Designs of Programming Models for Exascale Systemsinside-BigData.com
DK Panda from Ohio State University presented this deck at the Switzerland HPC Conference.
"This talk will focus on challenges in designing programming models and runtime environments for Exascale systems with millions of processors and accelerators to support various programming models. We will focus on MPI+X (PGAS - OpenSHMEM/UPC/CAF/UPC++, OpenMP, and CUDA) programming models by taking into account support for multi-core systems (KNL and OpenPower), high-performance networks, GPGPUs (including GPUDirect RDMA), and energy-awareness. Features and sample performance numbers from the MVAPICH2 libraries, will be presented."
Watch the video: http://wp.me/p3RLHQ-gCb
Learn more: http://hpcadvisorycouncil.com/events/2017/swiss-workshop/agenda.php
Sign up for our insideHPC Newsletter: http://insidehpc.com/newsletter
With the HPC Cloud facility, SURFsara offers self-service, dynamically scalable and fully configurable HPC systems to the Dutch academic community. Users have, for example, a free choice of operating system and software.
The HPC Cloud offers full control over a HPC cluster, with fast CPUs and high memory nodes and it is possible to attach terabytes of local storage to a compute node. Because of this flexibility, users can fully tailor the system for a particular application. Long-running and small compute jobs are equally welcome. Additionally, the system facilitates collaboration: users can share control over their virtual private HPC cluster with other users and share processing time, data and results. A portal with wiki, fora, repositories, issue system, etc. is offered for collaboration projects as well.
UberCloud HPC Experiment Introduction for Beginnershpcexperiment
UberCloud HPC Experiment Introduction for Beginners.
What is the HPC Experiment
How the HPC Experiment works
How to participate in the HPC Experiment
And an example project
We present applications of Azure Services such as Azure IaaS/PaaS and Azure RemoteApp in computational fluid dynamics and sparse linear algebra. We also present Microsoft Machine Learning Studio in prediction of the heating load in the buildings.
Have you heard that all in-memory databases are equally fast but unreliable, inconsistent and expensive? This session highlights in-memory technology that busts all those myths.
Redis, the fastest database on the planet, is not a simply in-memory key-value data-store; but rather a rich in-memory data-structure engine that serves the world’s most popular apps. Redis Labs’ unique clustering technology enables Redis to be highly reliable, keeping every data byte intact despite hundreds of cloud instance failures and dozens of complete data-center outages. It delivers full CP system characteristics at high performance. And with the latest Redis on Flash technology, Redis Labs achieves close to in-memory performance at 70% lower operational costs. Learn about the best uses of in-memory computing to accelerate everyday applications such as high volume transactions, real time analytics, IoT data ingestion and more.
For the full video of this presentation, please visit:
http://www.embedded-vision.com/platinum-members/embedded-vision-alliance/embedded-vision-training/videos/pages/sept-2016-member-meeting-mit
For more information about embedded vision, please visit:
http://www.embedded-vision.com
Vivienne Sze, Assistant Professor at MIT, delivers the presentation "Energy-efficient Hardware for Embedded Vision and Deep Convolutional Neural Networks" at the September 2016 Embedded Vision Alliance Member Meeting. Sze describes the results of her team's recent research on optimized hardware for deep learning.
Get Your Head in the Cloud - Lessons in GPU Computing with Schlumbergerinside-BigData.com
In this presentation from the GPU Technology Conference, Wyatt Gorman from Google and Abhishek Gupta from Schlumberger present: Get Your Head in the Cloud - Lessons in GPU Computing with Schlumberger.
"Demand for GPUs in High Performance Computing is only growing, and it is costly and difficult to keep pace in an entirely on-premise environment. We will hear from Schlumberger on why and how they are utilizing cloud-based GPU-enabled computing resources from Google Cloud to supply their users with the computing power they need, from exploration and modeling to visualization."
Watch the video: https://wp.me/p3RLHQ-kcl
Learn more: https://www.blog.google/products/google-cloud/schlumberger-chooses-gcp-to-deliver-new-oil-and-gas-technology-platform/
and
https://www.nvidia.com/en-us/gtc/
Optimize Single Particle Orbital (SPO) Evaluations Based on B-splinesIntel® Software
Orbital representations that are based on B-splines are widely used in quantum Monte Carlo (QMC) simulations of solids, which historically take as much as 50 percent of the total runtime. Random access to a large four-dimensional array make it challenging to efficiently use caches and wide vector units in modern CPUs. So, we present node-level optimizations of B-spline evaluations on multicore and manycore shared memory processors.
To increase single instruction multiple data (SIMD) efficiency and bandwidth utilization, we first apply data layout transformation from an array of structures (AoS) to a structure of arrays (SoA). Then, by blocking SoA objects, we optimize cache reuse and get sustained throughput for a range of problem sizes. We implement efficient nested threading in B-spline orbital evaluation kernels, paving the way towards enabling strong scaling of QMC simulations, resulting with performance enhancements. Finally, we employ roofline performance analysis to model the impacts of our optimizations.
The MEW Workshop is now established as a leading national event dedicated to distributed high performance scientific computing. The principle objective is to encourage close contact between the research communities from the Mathematics, Chemistry, Physics and Materials Programmes of EPSRC and the major vendors.
In this deck from Switzerland HPC Conference, Gunter Roeth from NVIDIA presents: Deep Learning on the SaturnV Cluster.
"Machine Learning is among the most important developments in the history of computing. Deep learning is one of the fastest growing areas of machine learning and a hot topic in both academia and industry. It has dramatically improved the state-of-the-art in areas such as speech recognition, computer vision, predicting the activity of drug molecules, and many other machine learning tasks. The basic idea of deep learning is to automatically learn to represent data in multiple layers of increasing abstraction, thus helping to discover intricate structure in large datasets. NVIDIA has invested in SaturnV, a large GPU-accelerated cluster, (#28 on the November 2016 Top500 list) to support internal machine learning projects. After an introduction to deep learning on GPUs, we will address a selection of open questions programmers and users may face when using deep learning for their work on these clusters."
Watch the video: http://wp.me/p3RLHQ-gDv
Learn more: http://www.nvidia.com/object/dgx-saturnv.html
and
http://hpcadvisorycouncil.com/events/2017/swiss-workshop/agenda.php
Sign up for our insideHPC Newsletter: http://insidehpc.com/newsletter
Microsoft Project Olympus AI Accelerator Chassis (HGX-1)inside-BigData.com
In this video from the Open Compute Summit, Siamak Tavallaei from Microsoft presents an overview of the Microsoft Project Olympus AI Accelerator Chassis, also known as the HGX-1.
Watch the presentation video: http://wp.me/p3RLHQ-guX
Sign up for our insideHPC Newsletter: http://insidehpc.com/newsletter
In this deck from the Switzerland HPC Conference, Francis Lam from Huawei presents: A Fresh Look at HPC from Huawei Enterprise.
"High performance computing is rapidly finding new uses in many applications and businesses, enabling the creation of disruptive products and services. Huawei, a global leader in information and communication technologies, brings a broad spectrum of innovative solutions to HPC. This talk examines Huawei's world class HPC solutions and explores creative new ways to solve HPC problems."
Watch the video: http://wp.me/p3RLHQ-gCV
Learn more: http://e.huawei.com/en/solutions/business-needs/data-center/high-performance-computing
and
http://www.hpcadvisorycouncil.com/events/2017/swiss-workshop/agenda.php
Sign up for our insideHPC Newsletter: http://insidehpc.com/newsletter
dCUDA: Distributed GPU Computing with Hardware Overlapinside-BigData.com
Torsten Hoefler from ETH Zurich presented this deck at the Switzerland HPC Conference.
"Over the last decade, CUDA and the underlying GPU hardware architecture have continuously gained popularity in various high-performance computing application domains such as climate modeling, computational chemistry, or machine learning. Despite this popularity, we lack a single coherent programming model for GPU clusters. We therefore introduce the dCUDA programming model, which implements device-side remote memory access with target notification. To hide instruction pipeline latencies, CUDA programs over-decompose the problem and over-subscribe the device by running many more threads than there are hardware execution units. Whenever a thread stalls, the hardware scheduler immediately proceeds with the execution of another thread ready for execution. This latency-hiding technique is key to make best use of the available hardware resources. With dCUDA, we apply latency hiding at cluster scale to automatically overlap computation and communication. Our benchmarks demonstrate perfect overlap for memory bandwidth-bound tasks and good overlap for compute-bound tasks."
Watch the video presentation: http://wp.me/p3RLHQ-gCB
In this deck, Gilad Shainer from Mellanox announces the world’s first HDR 200Gb/s data center interconnect solutions. "These 200Gb/s HDR InfiniBand solutions maintain Mellanox’s generation-ahead leadership while enabling customers and users to leverage an open, standards-based technology that maximizes application performance and scalability while minimizing overall data center total cost of ownership. Mellanox 200Gb/s HDR solutions will become generally available in 2017.
Watch the video presentation: http://insidehpc.com/2016/11/hdr-infiniband/
High-Performance and Scalable Designs of Programming Models for Exascale Systemsinside-BigData.com
DK Panda from Ohio State University presented this deck at the Switzerland HPC Conference.
"This talk will focus on challenges in designing programming models and runtime environments for Exascale systems with millions of processors and accelerators to support various programming models. We will focus on MPI+X (PGAS - OpenSHMEM/UPC/CAF/UPC++, OpenMP, and CUDA) programming models by taking into account support for multi-core systems (KNL and OpenPower), high-performance networks, GPGPUs (including GPUDirect RDMA), and energy-awareness. Features and sample performance numbers from the MVAPICH2 libraries, will be presented."
Watch the video: http://wp.me/p3RLHQ-gCb
Learn more: http://hpcadvisorycouncil.com/events/2017/swiss-workshop/agenda.php
Sign up for our insideHPC Newsletter: http://insidehpc.com/newsletter
With the HPC Cloud facility, SURFsara offers self-service, dynamically scalable and fully configurable HPC systems to the Dutch academic community. Users have, for example, a free choice of operating system and software.
The HPC Cloud offers full control over a HPC cluster, with fast CPUs and high memory nodes and it is possible to attach terabytes of local storage to a compute node. Because of this flexibility, users can fully tailor the system for a particular application. Long-running and small compute jobs are equally welcome. Additionally, the system facilitates collaboration: users can share control over their virtual private HPC cluster with other users and share processing time, data and results. A portal with wiki, fora, repositories, issue system, etc. is offered for collaboration projects as well.
UberCloud HPC Experiment Introduction for Beginnershpcexperiment
UberCloud HPC Experiment Introduction for Beginners.
What is the HPC Experiment
How the HPC Experiment works
How to participate in the HPC Experiment
And an example project
We present applications of Azure Services such as Azure IaaS/PaaS and Azure RemoteApp in computational fluid dynamics and sparse linear algebra. We also present Microsoft Machine Learning Studio in prediction of the heating load in the buildings.
These slides cover the pros and cons of implementing Memcached in a cloud environment, the basics and best practices of implementation, and how to get the most out of your investment with Memcached. We also introduce Gear6 Web Cache Server for the Cloud, the first commercial Memcached service for cloud platforms. The on-demand webcast can be accessed here:
http://www.gear6.com/memcached-resources/webinar-archive
Ip Networking Over Satelite Course SamplerJim Jenkins
This three-day course is designed for satellite engineers and managers in government and industry who need to increase their understanding of the Internet and how Internet Protocols (IP) can be used to transmit data and voice over satellites. IP has become the worldwide standard for data communications. Satellites extend the reach of the Internet and Intranets. Satellites deliver multicast content efficiently anywhere in the world. With these benefits come challenges. Satellite delay and bit errors can impact performance. Satellite links must be integrated with terrestrial networks. Space segment is expensive; there are routing and security issues. This course explains the techniques and architectures used to mitigate these challenges. Quantitative techniques for understanding throughput and response time are presented. System diagrams describe the satellite/terrestrial interface. The course notes provide an up-to-date reference. An extensive bibliography is supplied.
IBM Business Analytics and Optimization - Traffic Management with IBM InfoSph...IBM Sverige
Professor Haris och hans forskare på KTH har ett samarbete med de som utvecklar InfoSphere Streams på IBM Research. I detta projektet analyseras trafikdata från Stockholmsområdet för att se hur man kan nyttja informationen på bästa sätt för att styra trafiken smartare och informera resenärerna om hur man tar sig fram på bästa sätt.
Förutom själva Stockholmsområdet, så analyserar man trafiken till/från Arlanda. Bland annat vill man prediktera sannolikheten för att man kommer i tid till sin flygavgång på Arlanda beroende på vilken tid man skall åka och beroende på vilket transportsätt man väljer. KTH är vinnare till priset för en smartare planet 2010.
Talare: Haris N. Koutsopoulos, Professor and Head of Transportation and Logistics Division, KTH
Denna presentation hölls på ett seminariepass för Business Analytics & Optimization under IBM Software Day 2010.
Data-Intensive Computing for Competent Genetic Algorithms: A Pilot Study us...Xavier Llorà
Data-intensive computing has positioned itself as a valuable programming paradigm to efficiently approach problems requiring processing very large volumes of data. This paper presents a pilot study about how to apply the data-intensive computing paradigm to evolutionary computation algorithms. Two representative cases (selectorecombinative genetic algorithms and estimation of distribution algorithms) are presented, analyzed, and discussed. This study shows that equivalent data-intensive computing evolutionary computation algorithms can be easily developed, providing robust and scalable algorithms for the multicore-computing era. Experimental results show how such algorithms scale with the number of available cores without further modification.
4 Years Later: The Evolving Femto Ecosystem & Value PropositionContinuous Computing
This presentation was delivered at the Femtocells Americas event in December 2010 entitled, "4 Years Later: The Evolving Femto Ecosystem & Value Proposition".
Linea de scaners y unidades de captura de imagenes, lider mundial de fabricación alemana, image access, wide format scanners
http://www.PrintLAT.com
http://www.imageaccess.com
16.07.12 Analyzing Logs/Configs of 200'000 Systems with Hadoop (Christoph Sch...Swiss Big Data User Group
This talk was held at the second meeting of the Swiss Big Data User Group on July 16 at ETH Zürich. The topic of this meeting was: "NoSQL Storage: War Stories and Best Practices".
http://www.bigdata-usergroup.ch/item/296477
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
Le nuove frontiere dell'AI nell'RPA con UiPath Autopilot™UiPathCommunity
In questo evento online gratuito, organizzato dalla Community Italiana di UiPath, potrai esplorare le nuove funzionalità di Autopilot, il tool che integra l'Intelligenza Artificiale nei processi di sviluppo e utilizzo delle Automazioni.
📕 Vedremo insieme alcuni esempi dell'utilizzo di Autopilot in diversi tool della Suite UiPath:
Autopilot per Studio Web
Autopilot per Studio
Autopilot per Apps
Clipboard AI
GenAI applicata alla Document Understanding
👨🏫👨💻 Speakers:
Stefano Negro, UiPath MVPx3, RPA Tech Lead @ BSP Consultant
Flavio Martinelli, UiPath MVP 2023, Technical Account Manager @UiPath
Andrei Tasca, RPA Solutions Team Lead @NTT Data
A tale of scale & speed: How the US Navy is enabling software delivery from l...sonjaschweigert1
Rapid and secure feature delivery is a goal across every application team and every branch of the DoD. The Navy’s DevSecOps platform, Party Barge, has achieved:
- Reduction in onboarding time from 5 weeks to 1 day
- Improved developer experience and productivity through actionable findings and reduction of false positives
- Maintenance of superior security standards and inherent policy enforcement with Authorization to Operate (ATO)
Development teams can ship efficiently and ensure applications are cyber ready for Navy Authorizing Officials (AOs). In this webinar, Sigma Defense and Anchore will give attendees a look behind the scenes and demo secure pipeline automation and security artifacts that speed up application ATO and time to production.
We will cover:
- How to remove silos in DevSecOps
- How to build efficient development pipeline roles and component templates
- How to deliver security artifacts that matter for ATO’s (SBOMs, vulnerability reports, and policy evidence)
- How to streamline operations with automated policy checks on container images
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
PHP Frameworks: I want to break free (IPC Berlin 2024)Ralf Eggert
In this presentation, we examine the challenges and limitations of relying too heavily on PHP frameworks in web development. We discuss the history of PHP and its frameworks to understand how this dependence has evolved. The focus will be on providing concrete tips and strategies to reduce reliance on these frameworks, based on real-world examples and practical considerations. The goal is to equip developers with the skills and knowledge to create more flexible and future-proof web applications. We'll explore the importance of maintaining autonomy in a rapidly changing tech landscape and how to make informed decisions in PHP development.
This talk is aimed at encouraging a more independent approach to using PHP frameworks, moving towards a more flexible and future-proof approach to PHP development.
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdfPaige Cruz
Monitoring and observability aren’t traditionally found in software curriculums and many of us cobble this knowledge together from whatever vendor or ecosystem we were first introduced to and whatever is a part of your current company’s observability stack.
While the dev and ops silo continues to crumble….many organizations still relegate monitoring & observability as the purview of ops, infra and SRE teams. This is a mistake - achieving a highly observable system requires collaboration up and down the stack.
I, a former op, would like to extend an invitation to all application developers to join the observability party will share these foundational concepts to build on:
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
4. Software as a Service Google Apps,
(SaaS)
Salesforce.com
Platform as a Service
Web Google App Engine,
(PaaS)
Windows Azure
Infrastructure as a Service
(IaaS)
Amazon EC2
4
5. IaaS
•
• Pay-as-you-go
• “ ”
• Web
•
•
• IT
•
• Cloud bursting
5
10. 20,000
300
20,000
ACM/IEEE Supercomputing 2005 Best Paper Award
“Full Electron Calculation Beyond 20,000 Atoms:
Ground Electronic State of Photosynthetic Proteins”
11. ! NEB+Hybrid QM/MD
! GridRPC + MPI
! (1193 CPUs)
! 58 5000 QM
QM QM NCSA 64×4 CPUs for QM QM QM
SDSC 64×2 CPUs for QM
Purdue 64×4 CPUs for QM
USC 64×1 CPUs for QM
QM QM QM QM
NCSA
MPI USC MPI
RPC RPC Purdue
AIST SDSC
QM QM
QM QM
QM QM
MD MD RPC
QM QM RPC
MPI
MPI NEB scheduler
AIST F32 41×1 CPUs for MD Number of Execution
AIST F32 64×3 CPUs for QM
MD MD
AIST P32 64×4 CPUs for QM
MPI
system energy
end-1 end-2 reaction
0 Elapsed time
23. Rocks
Eucalyptus
OpenStack
OpenNebula
OS
RHEL5 1
VMM
Xen
Xen KVM
Xen KVM VMWare
Hyper-V
VM
VLAN
/home
libvirt VMM
VM
23
24. OpenNebula
• (Complutense University of
Madrid)
• Apache License 2.0
• C12G Labs
http://opennebula.org/about:about
(FP7)
24
25. OpenNebula
CLI or Sunstone GUI
global network
frontend
Sche
ONED
VM host 1 VM host 2 duler
VMM
VMM
/srv/cloud
/srv/cloud
SSH
/srv/cloud
SSH
|-- one
`-- images
VM
local network
VM NFS scp
25
26. OpenNebula
• CUI
VM
ID
Host
ID
• Sunstone
– Web GUI
26
27. Contextualization
• VM
VM
VM
•
–
– root
– SSH
VM
oned
– /etc/hosts /etc/resolv.
conf
– NFS
from OpenNebula Documentation
27
29. MAC_PREFIX:IP
• OpenNebula VM IP
MAC MAC
IP
• VM MAC IP
NIC
% onevnet show 1
(snip)
LEASES INFORMATION
LEASE=[IP=192.168.57.209, MAC=02:00:c0:a8:39:d1, USED=0, VID=-1]
IP
”02:00”
IP 4 octet 16
29
30. •
–
• OS OS
–
–
•
–
– VLAN
• OpenNebula 3.0
– PCI I/O
–
30
31. • VM
– OS
•
•
•
– VM SDSC
• P2V
• H/W
–
•
–
• ASC
31
50. PRAGMA Grid/Clouds
UZH
Switzerland CNIC JLU AIST
China China KISTI OsakaU
IndianaU
KMU UTsukuba
SDSC USA
LZU Korea Japan
China USA
ASGC
HKU NCHC
UoHyd HongKong
Taiwan
India
ASTI
NECTEC Philippines
CeNAT-ITCR
KU HCMUT Costa Rica
Thailand HUT
IOIT-Hanoi
UValle
MIMOS IOIT-HCM
Colombia
USM Vietnam
Malaysia
MU BESTGrid UChile
Australia New Zealand Chile
26 institutions in 17 countries/regions, 23 compute sites, 10VM sites
50
51. Put
all
together
Store
VM
images
in
Gfarm
systems
gFC
Run
vm-‐deploy
scripts
at
PRAGMA
Sites
gFC
VM
Image
Copy
VM
images
on
Demand
from
gFarm
VM
Image
copied
from
Condor
gFarm
slave
gFS
Modify/start
VM
instances
at
PRAGMA
sites
Master
copied
from
gFarm
slave
SDSC
(USA)
Manage
jobs
with
Condor
AIST
(Japan)
Rocks
Xen
OpenNebula
KVM
gFS
GFARM
Grid
File
gFC
System
(Japan)
gFC
VM
Image
AIST
QuickQuake
+
Condor
VM
Image
copied
from
copied
from
gFarm
slave gFS
NCHC
FmoRf
gFS
gFarm
slave
gFS
UCSD
Autodock
+
Condor
gFS
NCHC
(Taiwan)
IU
(USA)
OpenNebula
KVM
AIST
Web
Map
Service
+
Condor
Rocks
Xen
AIST
Geogrid
+
Bloss
AIST
HotSpot
+
Condor
gFC
gFS
gFS
gFC
VM
Image
VM
Image
copied
from
copied
from
gFarm
slave gFS
gFS
gFarm
slave
LZU
(China)
=
VM
deploy
Script
Osaka
(Japan)
Rocks
KVM
gFC
=
Grid
Farm
Client
Rocks
Xen
gFS
=
Grid
Farm
Server
51