This document summarizes GPU performance tests of the RiverFlow2D hydraulic model. Four test cases using real river meshes demonstrate speedups of up to 680 times faster than the CPU version. Later generation GPUs like the Tesla V100 and RTX 2080 Ti outperform older GPUs. While the Tesla V100 is fastest, the GTX 1080 Ti offers remarkable acceleration at lower cost. GPU acceleration allows simulating larger domains with finer meshes that were previously impractical due to runtimes.
Implementing AI: High Performance Architectures: A Universal Accelerated Comp...KTN
The Implementing AI: High Performance Architectures webinar, hosted by KTN and eFutures, was the fourth event in the Implementing AI webinar series.
The focus of the webinar was the impact of processing AI data on data centres - particularly from the technology perspective. Timothy Lanfear, Director of Solution Architecture and Engineering EMEA, NVIDIA, presented on a Universal Accelerated Computing Platform.
CGYRO Performance on Power9 CPUs and Volta GPUSIgor Sfiligoi
CGYRO, an Eulerian gyrokinetic solver for fusion plasma simulation has been ported and benchmarked on a Summit-like node, containing Power9 CPUs and Volta GPUs.
In this talk we present the porting experience and benchmark comparisons against nodes on other leadership systems.
Implementing AI: High Performance Architectures: A Universal Accelerated Comp...KTN
The Implementing AI: High Performance Architectures webinar, hosted by KTN and eFutures, was the fourth event in the Implementing AI webinar series.
The focus of the webinar was the impact of processing AI data on data centres - particularly from the technology perspective. Timothy Lanfear, Director of Solution Architecture and Engineering EMEA, NVIDIA, presented on a Universal Accelerated Computing Platform.
CGYRO Performance on Power9 CPUs and Volta GPUSIgor Sfiligoi
CGYRO, an Eulerian gyrokinetic solver for fusion plasma simulation has been ported and benchmarked on a Summit-like node, containing Power9 CPUs and Volta GPUs.
In this talk we present the porting experience and benchmark comparisons against nodes on other leadership systems.
BGE provides clients with the capability to integrate GPUs into the IBM BladeCenter ecosystem. This is ideal for clients running applications that can leverage the value of double precision performance and also value the RAS features of IBM BladeCenter.
The RAPIDS suite of software libraries gives you the freedom to execute end-to-end data science and analytics pipelines entirely on GPUs. It relies on NVIDIA® CUDA® primitives for low-level compute optimization, but exposes that GPU parallelism and high-bandwidth memory speed through user-friendly Python interfaces.
2015年9月18日開催 GTC Japan 2015 講演資料
エヌビディア合同会社
エンタープライズプロダクト事業部 シニアソリューションアーキテクト Jeremy Main
A walk through of the techniques to monitor existing workstation workloads to create data-driven estimates of recommended user density levels based on the GPU requirements, frame buffer utilization and other factors as well as methods to confirm GPU resource utilization to ensure excellent performing NVIDIA GRID vGPU enabled virtual machines.
Highlighted notes while studying Concurrent Data Structures:
GDDR5 SDRAM
Source: Wikipedia
GDDR5 SDRAM, an abbreviation for Graphics Double Data Rate 5 Synchronous Dynamic Random-Access Memory, is a modern type of synchronous graphics random-access memory (SGRAM) with a high bandwidth ("double data rate") interface designed for use in graphics cards, game consoles, and high-performance computing. [1] It is a type of GDDR SDRAM (graphics DDR SDRAM).
Wikipedia is a free online encyclopedia, created and edited by volunteers around the world and hosted by the Wikimedia Foundation.
Hire a Machine to Code - Michael Arthur Bucko & Aurélien NicolasWithTheBest
Bucko and Nicolas share their vision and products, as well as their explanation of what Deckard is. They provide insights from the software development team. They believe coding can resolve problems that we face. Specifically, source coding is the solution that they teach you and they have hopes for in fixing human errors.
Michael Arthur Bucko & Aurélien Nicolas
BGE provides clients with the capability to integrate GPUs into the IBM BladeCenter ecosystem. This is ideal for clients running applications that can leverage the value of double precision performance and also value the RAS features of IBM BladeCenter.
The RAPIDS suite of software libraries gives you the freedom to execute end-to-end data science and analytics pipelines entirely on GPUs. It relies on NVIDIA® CUDA® primitives for low-level compute optimization, but exposes that GPU parallelism and high-bandwidth memory speed through user-friendly Python interfaces.
2015年9月18日開催 GTC Japan 2015 講演資料
エヌビディア合同会社
エンタープライズプロダクト事業部 シニアソリューションアーキテクト Jeremy Main
A walk through of the techniques to monitor existing workstation workloads to create data-driven estimates of recommended user density levels based on the GPU requirements, frame buffer utilization and other factors as well as methods to confirm GPU resource utilization to ensure excellent performing NVIDIA GRID vGPU enabled virtual machines.
Highlighted notes while studying Concurrent Data Structures:
GDDR5 SDRAM
Source: Wikipedia
GDDR5 SDRAM, an abbreviation for Graphics Double Data Rate 5 Synchronous Dynamic Random-Access Memory, is a modern type of synchronous graphics random-access memory (SGRAM) with a high bandwidth ("double data rate") interface designed for use in graphics cards, game consoles, and high-performance computing. [1] It is a type of GDDR SDRAM (graphics DDR SDRAM).
Wikipedia is a free online encyclopedia, created and edited by volunteers around the world and hosted by the Wikimedia Foundation.
Hire a Machine to Code - Michael Arthur Bucko & Aurélien NicolasWithTheBest
Bucko and Nicolas share their vision and products, as well as their explanation of what Deckard is. They provide insights from the software development team. They believe coding can resolve problems that we face. Specifically, source coding is the solution that they teach you and they have hopes for in fixing human errors.
Michael Arthur Bucko & Aurélien Nicolas
Hybrid CPU GPU MATLAB Image Processing BenchmarkingDimitris Vayenas
An attempt to quantify the substantial performance improvement observed on Windows 8.1\ Nvidia GTX 780M\Intel HD 4600 via the latest NVIDIA Driver (326.01) that may help other users - particularly of the MATLAB Image Processing and Parallel Computing Toolboxes - to consider upgrading...
NVIDIA vGPU - Introduction to NVIDIA Virtual GPULee Bushen
Lee Bushen, Senior Solutions Architect at NVIDIA covers the basics of NVIDIA Virtual GPU.
- Why vGPU?
- How does it work?
- What are the main considerations for VDI?
- Which GPU is right for me?
- Which License do I need?
In this deck from the UK HPC Conference, Gunter Roeth from NVIDIA presents: Hardware & Software Platforms for HPC, AI and ML.
"Data is driving the transformation of industries around the world and a new generation of AI applications are effectively becoming programs that write software, powered by data, vs by computer programmers. Today, NVIDIA’s tensor core GPU sits at the core of most AI, ML and HPC applications, and NVIDIA software surrounds every level of such a modern application, from CUDA and libraries like cuDNN and NCCL embedded in every deep learning framework and optimized and delivered via the NVIDIA GPU Cloud to reference architectures designed to streamline the deployment of large scale infrastructures."
Watch the video: https://wp.me/p3RLHQ-l2Y
Learn more: http://nvidia.com
and
http://hpcadvisorycouncil.com/events/2019/uk-conference/agenda.php
Sign up for our insideHPC Newsletter: http://insidehpc.com/newsletter
DCSF 19 Accelerating Docker Containers with NVIDIA GPUsDocker, Inc.
Using the NVIDIA Container Runtime, many developers and enterprises have been developing, benchmarking and deploying deep learning (DL) frameworks, HPC and other GPU accelerated containers at scale for the last two years. In this talk, we will go over the architecture of the NVIDIA Container Runtime and discuss our recent close collaboration with Docker. The result of our collaboration with Docker is a seamless native integration of the runtime enabling Docker Engine 19.03 CE and the forthcoming Docker Enterprise release to run GPU accelerated containers. We will also highlight containerized NVIDIA drivers. This new feature eliminates the overhead of provisioning GPU machines and brings GPU support on container optimized operating systems, which either lack package managers for installing software or require all applications to run in containers. In this session, you will learn how GPU accelerated containers can be easily built and deployed through the use of driver containers and native support for GPUs in Docker 19.03. The session will include a demo of running a GPU accelerated deep learning container using the new CLI options in Docker 19.03 and containerized drivers. Running NVIDIA GPU accelerated containers with Docker has never been this easy!
1) NVIDIA-Iguazio Accelerated Solutions for Deep Learning and Machine Learning (30 mins):
About the speaker:
Dr. Gabriel Noaje, Senior Solutions Architect, NVIDIA
http://bit.ly/GabrielNoaje
2) GPUs in Data Science Pipelines ( 30 mins)
- GPU as a Service for enterprise AI
- A short demo on the usage of GPUs for model training and model inferencing within a data science workflow
About the speaker:
Anant Gandhi, Solutions Engineer, Iguazio Singapore. https://www.linkedin.com/in/anant-gandhi-b5447614/
Choosing a server solution that supports additional GPUs is a great option for offloading your HPC workloads and maximizing server performance. We found that the maximum configuration of the Dell PowerEdge C4130 with four NVIDIA Tesla K80 GPU accelerators delivered up to 9.3 times more performance than the Dell PowerEdge C4130 without GPUs. In addition, choosing the right server solution to support GPUs for your HPC workloads can deliver additional performance while maintaining reasonable GPU temperatures. We found that the maximum configuration of the Dell PowerEdge C4130 with four NVIDIA Tesla K80 GPU accelerators delivered up to 28 percent better performance than the maximum configuration of the Supermicro 1028GR-TR with three NVIDIA Tesla K80 GPU accelerators. In our testing of internal temperatures, we found the peak GPU temperature of the Dell PowerEdge C4130 in the maximum configuration to be up to 13 degrees cooler than the Supermicro 1028GR-TR maximum configuration.
The added performance of NVIDIA Tesla K80 GPUs can be valuable for organizations running anything from advanced algorithms to rendering 3D graphics. The new Dell PowerEdge C4130 server supports up to four GPUs, providing the platform your organization needs in its datacenter to handle these compute-intensive workloads. The design of the PowerEdge C4130 helps lower internal GPU temperatures via internal airflow—bringing another benefit for your organization by potentially extending hardware and chip life.
NVIDIA GPUs Power HPC & AI Workloads in Cloud with Univainside-BigData.com
In this deck from the Univa Breakfast Briefing at ISC 2018, Duncan Poole from NVIDIA describes how the company is accelerating HPC in the Cloud.
Learn more: https://www.nvidia.com/en-us/data-center/dgx-systems/
and
http://univa.com
Sign up for our insideHPC Newsletter: http://insidehpc.com/newsletter
Today’s groundbreaking scientific discoveries are taking place in HPC data centers. Using containers, researchers and scientists gain the flexibility to run HPC application containers on NVIDIA Volta-powered systems including Quadro-powered workstations, NVIDIA DGX Systems, and HPC clusters.
Robotics and Machine Learning: Working with NVIDIA Jetson KitsData Works MD
Data Works MD December 2019 - https://www.meetup.com/DataWorks/events/265823739/
Video is available at https://www.youtube.com/watch?v=EFHUdKTDRZM
Robotics and Machine Learning: Working with NVIDIA Jetson Kits
Interested in machine learning and AI? Do you want to learn more about high performance GPU programming and how it applies to Deep Learning? Patty Delafuente will introduce you to the Nvidia Jetson developer kits, discuss their applications, how to get started, and provide a live demonstration of NVIDIA® Jetson Nano™, an easy to use deep learning and robotics platform.
Patty Delafuente
Patty Delafuente, is a lead Data Scientist in the Advanced Data Analytics Lab at the Social Security Administration. She teaches evening classes for the University of Maryland Baltimore County’s graduate level Data Science Program. Patty is a member of the ‘MS in Analytics Advisory Board’ for Texas A&M University.
Patty holds a Master of Science in Analytics from Texas A&M University along with a Bachelor and Masters in Information Systems and holds numerous certifications. In 2017, she was awarded the Texas A&M Margaret Sheather Memorial Award in Analytics for her Capstone Project, “Using Decision Trees to Analyze Patterns in Disability Fraud.”
She has over twenty years of database engineering, business intelligence, and analytics experience.
Her interests include machine learning, text mining, and using GPUs to improve the performance of analyzing and processing big data. She is a certified Nvidia Instructor in the ‘Fundamentals of Deep Learning for Computer Vision’ and ‘Accelerated Computing with Python’. Patty can be reached LinkedIn at https://www.linkedin.com/in/pattydelafuente319/
This is a presentation I presented at NVIDIA AI Conference in Korea. It's about building the largest GPU - DGX-2, the most powerful supercomputer in one node.
Versions and Latest Releases
Version 16: with the newest release of version 16d, we introduce a new input style, called Desirable Inputs Model. In this new model, we allow some input style (called IGood) which are larger the better. Examples include number of electric vehicles in an environmental model, the number of test takers in vaccine development model, etc. For more details, go to newsletter 20.
A General Method for Estimating a Linear Structural Equation System
The substantially upgraded new version marks the golden jubilee of a seminal development in the history of Structure Equation Modeling (SEM). A little over a half century ago Professor Karl Jöreskog published a monograph in the Educational Testing Service (ETS) Research Bulletin series entitled A General Method for Estimating a Linear Structural Equation System, along with the LISREL software program.
祺荃企業有限公司 您可以信賴的軟體供應商
國內外原版軟體代理及經銷 | 教育訓練 | 軟體購買諮詢 | Devs Paradise | 線上商店(Store)
Cheer Chain Enterprise Co., Ltd. distributes and sells software with the aim of offering clients guidance when choosing software, as well as technical support !!!
Distribution of Software | Training Courses | Consulting Services
Focused Analysis of Qualitative Interviews with MAXQDA
Step by Step
Focused Analysis of Qualitative Interviews with MAXQDA
Authors: Stefan Rädiker, Udo Kuckartz
Pages: 125
Released: 2020
Language: English
ISBN: 978-3-948768072
DOI: 10.36192/978-3-948768072
All-in-One Website Security Scanner
Find and detect vulnerabilities at the earliest stage using Acunetix automated web vulnerability scannerFind vulnerabilities in your websites and web APIs
Find vulnerabilities in your websites and web APIs
Highest detection rating of over 4500 vulnerabilities in custom, commercial, and open source apps with nearly 0% false positives.
AcuSensor (IAST) allows you to find and test hidden inputs not discovered during black-box scanning (DAST)
Advanced Crawling & Authentication support gives you the ability to crawl JavaScript websites and SPAs
DEA-Solver-Pro Version 14d- Newsletter17
The latest release of version 14 is 14d, with a new feature SBM Bounded Model as an extention to SBM Max of version 13, which replaced SBM Variation model of version 12. In the real world, there are cases where input resources and/od output expansion are restricted by external constraints. SBM Bounded Model takes care of such situations, so that the outcome of SBM Bounded Model becomes more realistic than before. Note that these SBM models essentially represent KAIZEN improvement. For more details, go to newsletter 17.
NativeJ is a powerful Java EXE maker. The executable generated by NativeJ is uniquely customized to launch your Java application under Windows. NativeJ is not a compiler! Think of NativeJ-generated executables as supercharged "binary batch files"
需購買相關應用軟體請上 http://www.appcenter.com.tw/ or http://www.cheerchain.com.tw/
Edraw Max - All-In-One Diagram Software
Edraw Max is a versatile diagram software, with features that make it perfect not only for professional-looking flowcharts, org charts, network diagrams and mind maps, but also building plans, business charts, workflows, fashion designs, UML diagrams, electrical engineering diagrams, directional maps and database model diagrams.
EdrawSoft Edraw Max 特別版是一整合圖示繪製軟體,新穎小巧,功能強大,可以很方便的繪製各種專業的流程圖、組織結構圖、網路拓撲圖、傢俱設計圖、商業圖表等。
應用領域:流程圖、網路拓撲圖、組織結構圖、工作流程圖、UML,軟體設計、商業圖表、2D, 3D 圖形、計畫 / 報表、地圖,方向圖、資料庫等。
購買及下載請聯絡
祺荃企業有限公司 - 您可以信賴的軟體供應商
www.cheerchain.com.tw | info@cheerchain.com.tw
Tel : 886-4-2386-3559 Fax : 886-4-2386-3159
線上購買 : http://www.appcenter.com.tw/
Atlas.ti 8 質性分析軟體新功能介紹!
需購買相關應用軟體請上 http://www.appcenter.com.tw/ or http://www.cheerchain.com.tw/
購買請洽 祺荃企業有限公司-您可以信賴的軟體供應商
www.cheerchain.com.tw or www.appcenter.com.tw
Email : info@cheerchain.com.tw Phone : +8864-23863559
NEW VERSION OUT NOW! We are happy to announce that ATLAS.ti 8 is released now! Completely re-designed in nearly every aspect, ATLAS.ti 8 Windows is poised to set new standards for computer-assisted qualitative data analysis. What's new? Find out about the new powerfull features of ATLAS.ti 8 here http://bit.ly/2hDIK0H.
**ATLAS.ti licenses purchased after April 1, 2015 qualify for a FREE UPGRADE
New Features
These are some of the powerful new features:
Under the hood: Clean separation of data layer, application logic, and user interface, latest technology for safe and reliable performance.
Unicode throughout
Undo/Redo (100 steps)
Direct import of Twitter, Endnote, Evernote data
Powerful Visual Query Editor for creating and modifying SmartCodes and SmartGroups
Full project search (former “Word cruncher”) significantly improved with dynamic fade-in/fade-out hit categories
Elegant and trememdously useful new network layout options
Network groups
Memo comments
State-of-the-art, highly intuitive user interface with ribbons, tabbed views, flexible navigation areas.
All tool windows can be freely positioned
Multiple documents
More powerful “margin” than ever, many new interactive functions.
Features Yet To Come
At the time of the RC1 release, the following areas are still missing or incomplete:
Project exchange between ATLAS.ti Mac and ATLAS.ti Windows
Teamwork scenario with central, shared project directories
Non-English user interface
Some specific functionalities (see below)
Functionality still to be added:
Transcription
Document editing
Print documents with margin
Global filters
Interrater reliability
Relative values in code-doc table
XML converter
需購買相關應用軟體請上 http://www.appcenter.com.tw/ or http://www.cheerchain.com.tw/
購買請洽 祺荃企業有限公司-您可以信賴的軟體供應商
www.cheerchain.com.tw or www.appcenter.com.tw
Email : info@cheerchain.com.tw Phone : +8864-23863559
Maxqda12 features -detailed feature comparison for more information about each product
需購買相關應用軟體請上 http://www.appcenter.com.tw/ or http://www.cheerchain.com.tw/
Software Engineering, Software Consulting, Tech Lead.
Spring Boot, Spring Cloud, Spring Core, Spring JDBC, Spring Security,
Spring Transaction, Spring MVC,
Log4j, REST/SOAP WEB-SERVICES.
Enhancing Research Orchestration Capabilities at ORNL.pdfGlobus
Cross-facility research orchestration comes with ever-changing constraints regarding the availability and suitability of various compute and data resources. In short, a flexible data and processing fabric is needed to enable the dynamic redirection of data and compute tasks throughout the lifecycle of an experiment. In this talk, we illustrate how we easily leveraged Globus services to instrument the ACE research testbed at the Oak Ridge Leadership Computing Facility with flexible data and task orchestration capabilities.
Enhancing Project Management Efficiency_ Leveraging AI Tools like ChatGPT.pdfJay Das
With the advent of artificial intelligence or AI tools, project management processes are undergoing a transformative shift. By using tools like ChatGPT, and Bard organizations can empower their leaders and managers to plan, execute, and monitor projects more effectively.
Prosigns: Transforming Business with Tailored Technology SolutionsProsigns
Unlocking Business Potential: Tailored Technology Solutions by Prosigns
Discover how Prosigns, a leading technology solutions provider, partners with businesses to drive innovation and success. Our presentation showcases our comprehensive range of services, including custom software development, web and mobile app development, AI & ML solutions, blockchain integration, DevOps services, and Microsoft Dynamics 365 support.
Custom Software Development: Prosigns specializes in creating bespoke software solutions that cater to your unique business needs. Our team of experts works closely with you to understand your requirements and deliver tailor-made software that enhances efficiency and drives growth.
Web and Mobile App Development: From responsive websites to intuitive mobile applications, Prosigns develops cutting-edge solutions that engage users and deliver seamless experiences across devices.
AI & ML Solutions: Harnessing the power of Artificial Intelligence and Machine Learning, Prosigns provides smart solutions that automate processes, provide valuable insights, and drive informed decision-making.
Blockchain Integration: Prosigns offers comprehensive blockchain solutions, including development, integration, and consulting services, enabling businesses to leverage blockchain technology for enhanced security, transparency, and efficiency.
DevOps Services: Prosigns' DevOps services streamline development and operations processes, ensuring faster and more reliable software delivery through automation and continuous integration.
Microsoft Dynamics 365 Support: Prosigns provides comprehensive support and maintenance services for Microsoft Dynamics 365, ensuring your system is always up-to-date, secure, and running smoothly.
Learn how our collaborative approach and dedication to excellence help businesses achieve their goals and stay ahead in today's digital landscape. From concept to deployment, Prosigns is your trusted partner for transforming ideas into reality and unlocking the full potential of your business.
Join us on a journey of innovation and growth. Let's partner for success with Prosigns.
Navigating the Metaverse: A Journey into Virtual Evolution"Donna Lenk
Join us for an exploration of the Metaverse's evolution, where innovation meets imagination. Discover new dimensions of virtual events, engage with thought-provoking discussions, and witness the transformative power of digital realms."
Innovating Inference - Remote Triggering of Large Language Models on HPC Clus...Globus
Large Language Models (LLMs) are currently the center of attention in the tech world, particularly for their potential to advance research. In this presentation, we'll explore a straightforward and effective method for quickly initiating inference runs on supercomputers using the vLLM tool with Globus Compute, specifically on the Polaris system at ALCF. We'll begin by briefly discussing the popularity and applications of LLMs in various fields. Following this, we will introduce the vLLM tool, and explain how it integrates with Globus Compute to efficiently manage LLM operations on Polaris. Attendees will learn the practical aspects of setting up and remotely triggering LLMs from local machines, focusing on ease of use and efficiency. This talk is ideal for researchers and practitioners looking to leverage the power of LLMs in their work, offering a clear guide to harnessing supercomputing resources for quick and effective LLM inference.
Globus Compute wth IRI Workflows - GlobusWorld 2024Globus
As part of the DOE Integrated Research Infrastructure (IRI) program, NERSC at Lawrence Berkeley National Lab and ALCF at Argonne National Lab are working closely with General Atomics on accelerating the computing requirements of the DIII-D experiment. As part of the work the team is investigating ways to speedup the time to solution for many different parts of the DIII-D workflow including how they run jobs on HPC systems. One of these routes is looking at Globus Compute as a way to replace the current method for managing tasks and we describe a brief proof of concept showing how Globus Compute could help to schedule jobs and be a tool to connect compute at different facilities.
Unleash Unlimited Potential with One-Time Purchase
BoxLang is more than just a language; it's a community. By choosing a Visionary License, you're not just investing in your success, you're actively contributing to the ongoing development and support of BoxLang.
Climate Science Flows: Enabling Petabyte-Scale Climate Analysis with the Eart...Globus
The Earth System Grid Federation (ESGF) is a global network of data servers that archives and distributes the planet’s largest collection of Earth system model output for thousands of climate and environmental scientists worldwide. Many of these petabyte-scale data archives are located in proximity to large high-performance computing (HPC) or cloud computing resources, but the primary workflow for data users consists of transferring data, and applying computations on a different system. As a part of the ESGF 2.0 US project (funded by the United States Department of Energy Office of Science), we developed pre-defined data workflows, which can be run on-demand, capable of applying many data reduction and data analysis to the large ESGF data archives, transferring only the resultant analysis (ex. visualizations, smaller data files). In this talk, we will showcase a few of these workflows, highlighting how Globus Flows can be used for petabyte-scale climate analysis.
In 2015, I used to write extensions for Joomla, WordPress, phpBB3, etc and I ...Juraj Vysvader
In 2015, I used to write extensions for Joomla, WordPress, phpBB3, etc and I didn't get rich from it but it did have 63K downloads (powered possible tens of thousands of websites).
Gamify Your Mind; The Secret Sauce to Delivering Success, Continuously Improv...Shahin Sheidaei
Games are powerful teaching tools, fostering hands-on engagement and fun. But they require careful consideration to succeed. Join me to explore factors in running and selecting games, ensuring they serve as effective teaching tools. Learn to maintain focus on learning objectives while playing, and how to measure the ROI of gaming in education. Discover strategies for pitching gaming to leadership. This session offers insights, tips, and examples for coaches, team leads, and enterprise leaders seeking to teach from simple to complex concepts.
Large Language Models and the End of ProgrammingMatt Welsh
Talk by Matt Welsh at Craft Conference 2024 on the impact that Large Language Models will have on the future of software development. In this talk, I discuss the ways in which LLMs will impact the software industry, from replacing human software developers with AI, to replacing conventional software with models that perform reasoning, computation, and problem-solving.
Custom Healthcare Software for Managing Chronic Conditions and Remote Patient...Mind IT Systems
Healthcare providers often struggle with the complexities of chronic conditions and remote patient monitoring, as each patient requires personalized care and ongoing monitoring. Off-the-shelf solutions may not meet these diverse needs, leading to inefficiencies and gaps in care. It’s here, custom healthcare software offers a tailored solution, ensuring improved care and effectiveness.
Globus Connect Server Deep Dive - GlobusWorld 2024Globus
We explore the Globus Connect Server (GCS) architecture and experiment with advanced configuration options and use cases. This content is targeted at system administrators who are familiar with GCS and currently operate—or are planning to operate—broader deployments at their institution.
SOCRadar Research Team: Latest Activities of IntelBrokerSOCRadar
The European Union Agency for Law Enforcement Cooperation (Europol) has suffered an alleged data breach after a notorious threat actor claimed to have exfiltrated data from its systems. Infamous data leaker IntelBroker posted on the even more infamous BreachForums hacking forum, saying that Europol suffered a data breach this month.
The alleged breach affected Europol agencies CCSE, EC3, Europol Platform for Experts, Law Enforcement Forum, and SIRIUS. Infiltration of these entities can disrupt ongoing investigations and compromise sensitive intelligence shared among international law enforcement agencies.
However, this is neither the first nor the last activity of IntekBroker. We have compiled for you what happened in the last few days. To track such hacker activities on dark web sources like hacker forums, private Telegram channels, and other hidden platforms where cyber threats often originate, you can check SOCRadar’s Dark Web News.
Stay Informed on Threat Actors’ Activity on the Dark Web with SOCRadar!
In software engineering, the right architecture is essential for robust, scalable platforms. Wix has undergone a pivotal shift from event sourcing to a CRUD-based model for its microservices. This talk will chart the course of this pivotal journey.
Event sourcing, which records state changes as immutable events, provided robust auditing and "time travel" debugging for Wix Stores' microservices. Despite its benefits, the complexity it introduced in state management slowed development. Wix responded by adopting a simpler, unified CRUD model. This talk will explore the challenges of event sourcing and the advantages of Wix's new "CRUD on steroids" approach, which streamlines API integration and domain event management while preserving data integrity and system resilience.
Participants will gain valuable insights into Wix's strategies for ensuring atomicity in database updates and event production, as well as caching, materialization, and performance optimization techniques within a distributed system.
Join us to discover how Wix has mastered the art of balancing simplicity and extensibility, and learn how the re-adoption of the modest CRUD has turbocharged their development velocity, resilience, and scalability in a high-growth environment.
3. RiverFlow2D GPU Tests
iii
Contents
CONTENTS..................................................................................................................................................III
LIST OF FIGURES ......................................................................................................................................IV
LIST OF TABLES .........................................................................................................................................V
1 INTRODUCTION..................................................................................................................................1
2 TEST CASES.......................................................................................................................................2
2.1 TEST 1................................................................................................................................................................................2
Test 1 Results ...............................................................................................................................................................3
2.2 TEST 2................................................................................................................................................................................4
Test 2 Results ...............................................................................................................................................................5
2.3 TEST 3................................................................................................................................................................................6
Test 3 Results ...............................................................................................................................................................7
2.4 TEST 4................................................................................................................................................................................8
Test 4 Results ...............................................................................................................................................................9
3 COMMENTS.......................................................................................................................................10
4. RiverFlow2D GPU Tests
iv
List of Figures
Figure 1 RiverFlow2D Plus triangular-cell mesh...............................................................................................................................1
Figure 2 Main window at the end of the simulation for test 1 mesh 3...............................................................................................2
Figure 3 Test 1: Speed up of the GPU solution compared against the non-parallelized CPU version.............................................3
Figure 4 Main window at the end of the simulation for test 2 mesh 3...............................................................................................4
Figure 5 Test 2: Speed up of the GPU solution compared against the non-parallelized CPU version.............................................5
Figure 6 Main window at the end of the simulation for test 3 using Tesla K40 (top) and using Tesla K80 (bottom). .......................6
Figure 7 Test 3: Speed up of the GPU solution compared against the non-parallelized CPU version.............................................7
Figure 8 Main window at the end of the simulation for test 4 using Tesla K40 (top) and using Tesla K80 (bottom). ......................8
Figure 9 Test 4: Computational cost (in seconds) for the Tesla K80, Tesla P100, Tesla V100 and RTX 2080 Ti devices. ............9
5. RiverFlow2D GPU Tests
v
List of Tables
Table 1 Technical specification summary of NVIDIA GPU hardware. ..............................................................................................1
Table 2 Test 1: Run times for RiverFlow2D in different GPU hardware. Intel CPU corresponds to the non-parallelized model......3
Table 3 Test 2: Run times for RiverFlow2D in different GPU hardware. Intel CPU corresponds to the non-parallelized model.....5
Table 4 Test 3: Run times for RiverFlow2D in different GPU hardware. Intel CPU corresponds to the non-parallelized model......7
Table 5 Test 4: Run times for RiverFlow2D in different GPU hardware. Intel CPU corresponds to the non-parallelized model......9
6.
7. RiverFlow2D GPU Tests
1
1 Introduction
RiverFlow2D, is suite of two-dimensional finite-volume models for rivers, floodplains and estuaries that include flow
hydrodynamics, and add-on modules for erosion and deposition simulations, mud and debris flows, and pollutant
dispersion. RiverFlow2D can route floods in rivers and simulate inundation over complex terrain at high resolution
and with remarkable stability, accuracy and speed. The use of adaptive triangular-cell meshes enables the flow field
to be resolved around key features in complex river environments. The GPU version allows performing hydrodynamic
computations up to than 680 times faster than non-parallelized models. RiverFlow2D hydraulic simulation core has
been developed in collaboration with the Computational Hydraulics Group of the University of Zaragoza in
Spain.
This document presents several tests to demonstrate the performance of the RiverFlow2D GPU model on a
variety of real project applications using several meshes with different resolutions and utilizing various NVIDIA
GPU hardware cards (see Table 1).
Table 1 Technical specification summary of NVIDIA GPU hardware.
Tesla
K40
Tesla K80 GTX 1080 Ti
Tesla
P100
Tesla V100 RTX 2080 Ti
CUDA cores 2,880 2 x 2,496 3,584 3,584 5,120 4,352
Memory 12 Gb 24 Gb 11 Gb 16 Gb 16 Gb 11 Gb
Note: The sequential version of the code was run on a computer with an Intel Core i7-3820 @ 3.60 GHz CPU.
In the tests described in this document we report runtimes for each application and calculate model speed
ups with respect to the non-parallelized CPU model (using one core), which is the standard procedure to
compute speedups. For instance, if the speedup is reported to be 100, it means that the model performs
100 times faster than the non-parallelized version.
Figure 1 RiverFlow2D Plus triangular-cell mesh.
8. RiverFlow2D GPU Tests
2
2 Test Cases
We present different tests to illustrate the performance of the RiverFlow2D GPU model in five real
applications using various GPU cards.
2.1 Test 1
The first test case involves the model application to a short reach of the Green River (USA) using three mesh
resolutions: 19,079 cells (Mesh 3), 154,880 cells (Mesh 3), and 1,878,607 (Mesh 3).
Figure 2 Main window at the end of the simulation for test 1 mesh 3.
9. RiverFlow2D GPU Tests
3
Test 1 Results
Table 2 Test 1: Run times for RiverFlow2D in different GPU hardware. Intel CPU corresponds to the non-parallelized
model.
Mesh No. Cells Intel CPU Tesla K80
GTX 1080
Ti
Tesla P100 Tesla V100
RTX 2080
Ti
Max
Speedup
Mesh1 19,079 00:00:08:14 00:00:00:18 00:00:00:38 00:00:00:13 00:00:00:11 00:00:00:46 45x
Mesh2 154,880 00:03:23:47 00:00:02:38 00:00:02:44 00:00:01:24 00:00:00:51 00:00:03:07 238x
Mesh3 1,878,607 08:23:17:47 00:01:28:04 00:01:08:28 00:00:33:40 00:00:18:49 00:01:00:39 687x
Figure 3 Test 1: Speed up of the GPU solution compared against the non-parallelized CPU version.
27.44
13.00
38.00 44.91
10.74
77.39 74.55
145.56
239.75
65.39
146.68
188.67
383.70
686.51
212.99
0.00
100.00
200.00
300.00
400.00
500.00
600.00
700.00
800.00
Tesla K80 GTX 1080 Ti Tesla P100 Tesla V100 RTX 2080 Ti
Axis Title
Mesh1 Mesh2 Mesh3
10. RiverFlow2D GPU Tests
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2.2 Test 2
The second test is about an application of a hydraulic structure in New Orleans at high resolution. We present
results for three meshes: 21,001 Cells in Mesh 1, 539,177 cells in Mesh 2 and 1,640,606 Cells in Mesh 3. The
project was provided by Stantec.
Figure 4 Main window at the end of the simulation for test 2 mesh 3.
11. RiverFlow2D GPU Tests
5
Test 2 Results
Table 3 Test 2: Run times for RiverFlow2D in different GPU hardware. Intel CPU corresponds to the non-parallelized
model.
Mesh No. Cells Intel CPU Tesla K80
GTX 1080
Ti
Tesla P100 Tesla V100
RTX 2080
Ti
Max
Speedup
Mesh 1 21,001 00:00:37:07 00:00:01:24 00:00:02:42 00:00:00:53 00:00:00:44 00:00:03:15 51x
Mesh 2 539,177 02:22:39:24 00:00:38:12 00:00:35:30 00:00:16:36 00:00:09:49 00:00:32:08 432x
Mesh 3 1,640,606 16:05:34:31 00:03:18:32 00:02:37:37 00:01:15:36 00:00:40:55 00:02:17:59 571x
Figure 5 Test 2: Speed up of the GPU solution compared against the non-parallelized CPU version.
26.51
13.75
42.02 50.61
11.42
110.98 119.42
255.39
431.86
131.93117.74
148.30
309.19
571.27
169.40
0.00
100.00
200.00
300.00
400.00
500.00
600.00
Tesla K80 GTX 1080 Ti Tesla P100 Tesla V100 RTX 2080 Ti
Mesh1 Mesh2 Mesh3
12. RiverFlow2D GPU Tests
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2.3 Test 3
This test case represents an event for the simulation of a river in California (USA) including 357,611 cells. The
event covers a period of 6 days and 23 hours.
Figure 6 Main window at the end of the simulation for test 3 using Tesla K40 (top) and using Tesla K80 (bottom).
13. RiverFlow2D GPU Tests
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Test 3 Results
Table 4 Test 3: Run times for RiverFlow2D in different GPU hardware. Intel CPU corresponds to the non-parallelized
model.
No. Cells Intel CPU Tesla K80
GTX 1080
Ti
Tesla P100 Tesla V100
RTX 2080
Ti
Max
Speedup
357,611 06:00:30:01 00:01:51:47 00:01:47:10 00:00:49:49 00:00:34:38 00:01:59:56 250x
Figure 7 Test 3: Speed up of the GPU solution compared against the non-parallelized CPU version.
77.56 80.90
174.04
250.34
72.29
0.00
50.00
100.00
150.00
200.00
250.00
300.00
Tesla K80 GTX 1080 Ti Tesla P100 Tesla V100 RTX 2080 Ti
14. RiverFlow2D GPU Tests
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2.4 Test 4
This test reports on results of an ongoing collaboration with the National Oceanic and Atmospheric
Administration (NOAA) of the USA. It shows a simulation of 420-mile reach of the Red River of the North located
in Minnesota (USA). The event involves the routing of 3-month hydrographs.
Figure 8 Main window at the end of the simulation for test 4 using Tesla K40 (top) and using Tesla K80 (bottom).
15. RiverFlow2D GPU Tests
9
Test 4 Results
The computer times of the non-parallelized CPU model is impractical for this test. Therefore, only the
RiverFlow2D GPU model was used.
Table 5 Test 4: Run times for RiverFlow2D in different GPU hardware. Intel CPU corresponds to the non-parallelized
model.
No. of cells Tesla K80 Tesla P100 Tesla V100
RTX 2080
Ti
4,616,546 00:20:50:46 01:02:55:42 01:02:21:04 00:12:22:54
Figure 9 Test 4: Computational cost (in seconds) for the Tesla K80, Tesla P100, Tesla V100 and RTX 2080 Ti devices.
75046
33972
22948
44574
Tesla K80 Tesla P100 Tesla V100 RTX 2080 Ti
16. RiverFlow2D GPU Tests
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3 Comments
This report presents performance results of the Riverflow2D GPU model in several NVIDIA GPUs including the
latest generation RTX, Tesla P100 and V100 cards. While the Tesla V100 is still the clear winner of the tested
devices, the NVIDIA GTX 1080 Ti card is much lower in costs and its acceleration capabilities are also
remarkable. The latest benchmarks include the RTX 2080 Ti, for which the performance gain is almost
negligible compared to the GTX 1080 Ti, therefore cannot be recommended as the best low cost solution. This
was a surprise for us since we usually see about a 20-25% increase in speed between generations.
As demonstrated in the tests presented in this document, the remarkable performance of the RiverFlow2D GPU
has several implications including:
• Computer run times are reduced from days to a few hours, or from hours to minutes, and from minutes
to seconds in some cases.
• The RiverFlow2D GPU allows evaluating river flooding simulations of large river reaches that were
impractical until recently due to excessive runtimes.
• The use of GPU technology developed in the RiverFlow2D code also allows using models with large
resolution meshes involving millions of cells.
• The emergence of Pay-per-Use Cloud Services such as the Google Cloud where all of the tested cards
are available at very attractive costs, facilitates the use of the RiverFlow2D GPU model for a wide range
or applications.