A brief technical overview about GPU power consumption and performance, with references to the latest architecture developed by Nvidia: Maxwell and Tegra X1.
Co-Author: Pietro Piscione (https://www.linkedin.com/pub/pietro-piscione/84/b37/926)
In this video, Jeff Larkin from NVIDIA presents: Unified Memory on Summit.
"The biggest problems in science require supercomputers of unprecedented capability. That’s why the US Department of Energy’s Oak Ridge National Laboratory (ORNL) launched Summit, a system 8 times more powerful than ORNL’s previous top-ranked system Titan. Summit is providing scientists with incredible computing power to solve challenges in energy, artificial intelligence, human health, and other research areas, that were simply out of reach until now. These discoveries will help shape our understanding of the universe, bolster US economic competitiveness, and contribute to a better future.
The Summit Application Readiness Workshop had the primary objective of providing the detailed technical information and hands-on help required for select application teams to meet the scalability and performance metrics required for Early Science proposals. It is the expectation that at the time of the workshop, Summit Phase I will be available in a configuration that will allow the teams to demonstrate these metrics using representative science runs. This will be an important milestone for the projects, and a requisite for a successful Early Science proposal. Technical representatives from the IBM/NVIDIA Center of Excellence will be delivering a few plenary presentations, but most of the time will be set aside for the extended application teams to carry out hands-on technical work on Summit."
Learn more: https://www.olcf.ornl.gov/summit-application-readiness-workshop/
Sign up for our insideHPC Newsletter: http://insidehpc.com/newsletter
This webinar by Dov Nimratz (Senior Solution Architect, Consultant, GlobalLogic) was delivered at Embedded Community Webinar #1 on July 7, 2020.
Webinar agenda:
- CPU / GPU / TPU architectures
- Historical context
- CPU and their variations
- GPU or gin in a bottle for artificial intelligence tasks
- TPU architecture specialized artificial intelligence accelerator
- What's next in technology
More details and presentation: https://www.globallogic.com/ua/about/events/embedded-community-webinar-1/
This Presentation was prepared by Abdussamad Muntahi for the Seminar on High Performance Computing on 11/7/13 (Thursday) Organized by BRAC University Computer Club (BUCC) in collaboration with BRAC University Electronics and Electrical Club (BUEEC).
For the full video of this presentation, please visit:
https://www.embedded-vision.com/platinum-members/renesas/embedded-vision-training/videos/pages/may-2019-embedded-vision-summit
For more information about embedded vision, please visit:
http://www.embedded-vision.com
Yoshio Sato, Senior Product Marketing Manager in the Industrial Business Unit at Renesas, presents the "Dynamically Reconfigurable Processor Technology for Vision Processing" tutorial at the May 2019 Embedded Vision Summit.
The Dynamically Reconfigurable Processing (DRP) block in the Arm Cortex-A9 based RZ/A2M MPU accelerates image processing algorithms with spatially pipelined, time-multiplexed, reconfigurable- hardware compute resources. This hybrid ARM/DRP architecture combines the economy, flexibility and ease-of-use of microprocessors with the high throughput and low latency of performance- optimized hardware.
DRP technology achieves silicon area efficiency by dividing large data paths into sub- blocks that can be swapped into the DRP hardware on each clock cycle to accelerate multiple complex algorithms while avoiding the cost and power penalties associated with large FPGAs. Pre-built libraries and a C-language programming environment deliver these benefits without the need for hardware design expertise. Designs can be iteratively enhanced through pre-production and even after mass-market deployment.
In this presentation, Sato examines the DRP block’s architecture and operation, presents benchmarks demonstrating performance up to 20x greater than traditional CPUs and introduces resources for developing DRP-based embedded vision systems with the RZ/A2M MPU.
In this video, Jeff Larkin from NVIDIA presents: Unified Memory on Summit.
"The biggest problems in science require supercomputers of unprecedented capability. That’s why the US Department of Energy’s Oak Ridge National Laboratory (ORNL) launched Summit, a system 8 times more powerful than ORNL’s previous top-ranked system Titan. Summit is providing scientists with incredible computing power to solve challenges in energy, artificial intelligence, human health, and other research areas, that were simply out of reach until now. These discoveries will help shape our understanding of the universe, bolster US economic competitiveness, and contribute to a better future.
The Summit Application Readiness Workshop had the primary objective of providing the detailed technical information and hands-on help required for select application teams to meet the scalability and performance metrics required for Early Science proposals. It is the expectation that at the time of the workshop, Summit Phase I will be available in a configuration that will allow the teams to demonstrate these metrics using representative science runs. This will be an important milestone for the projects, and a requisite for a successful Early Science proposal. Technical representatives from the IBM/NVIDIA Center of Excellence will be delivering a few plenary presentations, but most of the time will be set aside for the extended application teams to carry out hands-on technical work on Summit."
Learn more: https://www.olcf.ornl.gov/summit-application-readiness-workshop/
Sign up for our insideHPC Newsletter: http://insidehpc.com/newsletter
This webinar by Dov Nimratz (Senior Solution Architect, Consultant, GlobalLogic) was delivered at Embedded Community Webinar #1 on July 7, 2020.
Webinar agenda:
- CPU / GPU / TPU architectures
- Historical context
- CPU and their variations
- GPU or gin in a bottle for artificial intelligence tasks
- TPU architecture specialized artificial intelligence accelerator
- What's next in technology
More details and presentation: https://www.globallogic.com/ua/about/events/embedded-community-webinar-1/
This Presentation was prepared by Abdussamad Muntahi for the Seminar on High Performance Computing on 11/7/13 (Thursday) Organized by BRAC University Computer Club (BUCC) in collaboration with BRAC University Electronics and Electrical Club (BUEEC).
For the full video of this presentation, please visit:
https://www.embedded-vision.com/platinum-members/renesas/embedded-vision-training/videos/pages/may-2019-embedded-vision-summit
For more information about embedded vision, please visit:
http://www.embedded-vision.com
Yoshio Sato, Senior Product Marketing Manager in the Industrial Business Unit at Renesas, presents the "Dynamically Reconfigurable Processor Technology for Vision Processing" tutorial at the May 2019 Embedded Vision Summit.
The Dynamically Reconfigurable Processing (DRP) block in the Arm Cortex-A9 based RZ/A2M MPU accelerates image processing algorithms with spatially pipelined, time-multiplexed, reconfigurable- hardware compute resources. This hybrid ARM/DRP architecture combines the economy, flexibility and ease-of-use of microprocessors with the high throughput and low latency of performance- optimized hardware.
DRP technology achieves silicon area efficiency by dividing large data paths into sub- blocks that can be swapped into the DRP hardware on each clock cycle to accelerate multiple complex algorithms while avoiding the cost and power penalties associated with large FPGAs. Pre-built libraries and a C-language programming environment deliver these benefits without the need for hardware design expertise. Designs can be iteratively enhanced through pre-production and even after mass-market deployment.
In this presentation, Sato examines the DRP block’s architecture and operation, presents benchmarks demonstrating performance up to 20x greater than traditional CPUs and introduces resources for developing DRP-based embedded vision systems with the RZ/A2M MPU.
Virtualization with KVM (Kernel-based Virtual Machine)Novell
As a technical preview, SUSE Linux Enterprise Server 11 contains KVM, which is the next-generation virtualization software delivered with the Linux kernel. In this technical session we will demonstrate how to set up SUSE Linux Enterprise Server 11 for KVM, install some virtual machines and deal with different storage and networking setups.
To demonstrate live migration we will also show a distributed replicated block device (DRBD) setup and a setup based on iSCSI and OCFS2, which are included in SUSE Linux Enterprise Server 11 and SUSE Linux Enterprise 11 High Availability Extension.
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
AMD has been away from the HPC space for a while, but now they are coming back in a big way with an open software approach to GPU computing. The Radeon Open Compute Platform (ROCm) was born from the Boltzman Initiative announced last year at SC15. Now available on GitHub, the ROCm Platform bringing a rich foundation to advanced computing by better integrating the CPU and GPU to solve real-world problems.
"We are excited to present ROCm, the first open-source HPC/ultrascale-class platform for GPU computing that’s also programming-language independent. We are bringing the UNIX philosophy of choice, minimalism and modular software development to GPU computing. The new ROCm foundation lets you choose or even develop tools and a language run time for your application."
Watch the video presentation: http://wp.me/p3RLHQ-fJT
Learn more: https://radeonopencompute.github.io/
Sign up for our insideHPC Newsletter: http://insidehpc.com/newsletter
Modular by Design: Supermicro’s New Standards-Based Universal GPU ServerRebekah Rodriguez
In this webinar, members of the Server Solution Team as well as a member of Supermicro’s Product Office will discuss Supermicro’s Universal GPU Server, the server’s modular, standards-based design, the important role of OCP Accelerator Module (OAM) form factor, and Universal Baseboard (UBB) in the system, as well as touching on AMD's next generation HPC accelerator. In addition, we will get some insights into trends in the HPC and AI/Machine Learning space, including the different software platforms and best practices that are driving innovation in our industry and daily lives. In particular: • Tools to enable use of the high performance hardware for HPC and Deep Learning applications • Tools to enable use of multiple GPUs, including RDMA, to solve highly demanding HPC and deep learning models, such as BERT • Running applications in containers with AMD’s next generation GPU system
In the CXL Forum Theater at SC23 hosted by MemVerge, the Open Compute Project provided an overview of CXL, as well as CXL-related hardware and software projects at OCP
Introduction to Linux Kernel by Quontra SolutionsQUONTRASOLUTIONS
Course Duration: 30-35 hours Training + Assignments + Actual Project Based Case Studies
Training Materials: All attendees will receive,
Assignment after each module, Video recording of every session
Notes and study material for examples covered.
Access to the Training Blog & Repository of Materials
Pre-requisites:
Basic Computer Skills and knowledge of IT.
Training Highlights
* Focus on Hands on training.
* 30 hours of Assignments, Live Case Studies.
* Video Recordings of sessions provided.
* One Problem Statement discussed across the whole training program.
* Resume prep, Interview Questions provided.
WEBSITE: www.QuontraSolutions.com
Contact Info: Phone +1 404-900-9988(or) Email - info@quontrasolutions.com
High Performance Computing Presentationomar altayyan
The Presentation Delivered on 3-6-2018 in the Data Mining Course, AI Specialization, at the Faculty of Information Technology Engineering Damascus University
Paper Link:
https://shamra.sy/academia/show/5b0c790de9fc6
The Google File System (GFS) presented in 2003 is the inspiration for the Hadoop Distributed File System (HDFS). Let's take a deep dive into GFS to better understand Hadoop.
Modular by Design: Supermicro’s New Standards-Based Universal GPU ServerRebekah Rodriguez
In this webinar, members of the Server Solution Team as well as a member of Supermicro’s Product Office will discuss Supermicro’s Universal GPU Server, the server’s modular, standards-based design, the important role of OCP Accelerator Module (OAM) form factor, and Universal Baseboard (UBB) in the system, as well as touching on AMD's next generation HPC accelerator. In addition, we will get some insights into trends in the HPC and AI/Machine Learning space, including the different software platforms and best practices that are driving innovation in our industry and daily lives. In particular: • Tools to enable use of the high performance hardware for HPC and Deep Learning applications • Tools to enable use of multiple GPUs, including RDMA, to solve highly demanding HPC and deep learning models, such as BERT • Running applications in containers with AMD’s next generation GPU system
Virtualization with KVM (Kernel-based Virtual Machine)Novell
As a technical preview, SUSE Linux Enterprise Server 11 contains KVM, which is the next-generation virtualization software delivered with the Linux kernel. In this technical session we will demonstrate how to set up SUSE Linux Enterprise Server 11 for KVM, install some virtual machines and deal with different storage and networking setups.
To demonstrate live migration we will also show a distributed replicated block device (DRBD) setup and a setup based on iSCSI and OCFS2, which are included in SUSE Linux Enterprise Server 11 and SUSE Linux Enterprise 11 High Availability Extension.
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
AMD has been away from the HPC space for a while, but now they are coming back in a big way with an open software approach to GPU computing. The Radeon Open Compute Platform (ROCm) was born from the Boltzman Initiative announced last year at SC15. Now available on GitHub, the ROCm Platform bringing a rich foundation to advanced computing by better integrating the CPU and GPU to solve real-world problems.
"We are excited to present ROCm, the first open-source HPC/ultrascale-class platform for GPU computing that’s also programming-language independent. We are bringing the UNIX philosophy of choice, minimalism and modular software development to GPU computing. The new ROCm foundation lets you choose or even develop tools and a language run time for your application."
Watch the video presentation: http://wp.me/p3RLHQ-fJT
Learn more: https://radeonopencompute.github.io/
Sign up for our insideHPC Newsletter: http://insidehpc.com/newsletter
Modular by Design: Supermicro’s New Standards-Based Universal GPU ServerRebekah Rodriguez
In this webinar, members of the Server Solution Team as well as a member of Supermicro’s Product Office will discuss Supermicro’s Universal GPU Server, the server’s modular, standards-based design, the important role of OCP Accelerator Module (OAM) form factor, and Universal Baseboard (UBB) in the system, as well as touching on AMD's next generation HPC accelerator. In addition, we will get some insights into trends in the HPC and AI/Machine Learning space, including the different software platforms and best practices that are driving innovation in our industry and daily lives. In particular: • Tools to enable use of the high performance hardware for HPC and Deep Learning applications • Tools to enable use of multiple GPUs, including RDMA, to solve highly demanding HPC and deep learning models, such as BERT • Running applications in containers with AMD’s next generation GPU system
In the CXL Forum Theater at SC23 hosted by MemVerge, the Open Compute Project provided an overview of CXL, as well as CXL-related hardware and software projects at OCP
Introduction to Linux Kernel by Quontra SolutionsQUONTRASOLUTIONS
Course Duration: 30-35 hours Training + Assignments + Actual Project Based Case Studies
Training Materials: All attendees will receive,
Assignment after each module, Video recording of every session
Notes and study material for examples covered.
Access to the Training Blog & Repository of Materials
Pre-requisites:
Basic Computer Skills and knowledge of IT.
Training Highlights
* Focus on Hands on training.
* 30 hours of Assignments, Live Case Studies.
* Video Recordings of sessions provided.
* One Problem Statement discussed across the whole training program.
* Resume prep, Interview Questions provided.
WEBSITE: www.QuontraSolutions.com
Contact Info: Phone +1 404-900-9988(or) Email - info@quontrasolutions.com
High Performance Computing Presentationomar altayyan
The Presentation Delivered on 3-6-2018 in the Data Mining Course, AI Specialization, at the Faculty of Information Technology Engineering Damascus University
Paper Link:
https://shamra.sy/academia/show/5b0c790de9fc6
The Google File System (GFS) presented in 2003 is the inspiration for the Hadoop Distributed File System (HDFS). Let's take a deep dive into GFS to better understand Hadoop.
Modular by Design: Supermicro’s New Standards-Based Universal GPU ServerRebekah Rodriguez
In this webinar, members of the Server Solution Team as well as a member of Supermicro’s Product Office will discuss Supermicro’s Universal GPU Server, the server’s modular, standards-based design, the important role of OCP Accelerator Module (OAM) form factor, and Universal Baseboard (UBB) in the system, as well as touching on AMD's next generation HPC accelerator. In addition, we will get some insights into trends in the HPC and AI/Machine Learning space, including the different software platforms and best practices that are driving innovation in our industry and daily lives. In particular: • Tools to enable use of the high performance hardware for HPC and Deep Learning applications • Tools to enable use of multiple GPUs, including RDMA, to solve highly demanding HPC and deep learning models, such as BERT • Running applications in containers with AMD’s next generation GPU system
Computing Performance: On the Horizon (2021)Brendan Gregg
Talk by Brendan Gregg for USENIX LISA 2021. https://www.youtube.com/watch?v=5nN1wjA_S30 . "The future of computer performance involves clouds with hardware hypervisors and custom processors, servers running a new type of BPF software to allow high-speed applications and kernel customizations, observability of everything in production, new Linux kernel technologies, and more. This talk covers interesting developments in systems and computing performance, their challenges, and where things are headed."
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/
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.
How to achieve 95%+ Accurate power measurement during architecture exploration? Deepak Shankar
During the conceptualization and architectural exploration phases, it is crucial to assess the power budget.
Would you like to accurately measure the:
1. Power consumed for a proposed embedded software or firmware?
2. Savings of a Power Management Algorithm prior to development?
3. Power impact of hardware configuration change?
4. Trade-off between Power and Performance?
5. Temperature, heat, peak power and cumulative power?
The Visual Effect Graph gives artists of all experience levels the power to create amazing particle VFX. In this intermediate-level session, Julien Fryer and Vlad Neykov from our development team will give you a sneak peek into how to generate millions of GPU-based particles in real-time using the Visual Effects Graph's toolset.
Vlad Neykov - Unity Technologies
Julien Fryer - Unity Technologies
Introduction to Software Defined Visualization (SDVis)Intel® Software
Software defined visualization (SDVis) is an open-source initiative from Intel and industry collaborators. Improve the visual fidelity, performance, and efficiency of prominent visualization solutions, while supporting the rapidly growing big data use on workstations through high-performance computing (HPC) on supercomputing clusters without memory limitations and cost of GPU-based solutions.
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1. Power Consumption and
Performance trends on GPUs
Computer Architecture
Authors:
Piscione Pietro
Villardita Alessio
A.Y. 2014/2015
Degree: Computer Engineering
3. Why GPU ?
● Multimedia and
general purpose
applications
and recently, also
● High Performance
Computing applications,
"autonomous machines"
and automotive
CAD and
3D apps
Office
and PDF
readers
Multimedia
Audio/Video
Browsers
4. Power Consumption Overview
Domain
GPU power
consumption
Desktop and Workstation
(no mobility) 300W (50%)
Notebook
(mobility)
50W (71%)
And the smartphones ?
6. GPU power consumption on mobile
How much power
does a mobile
application require
in order to execute?
Why is the GPU so
“energy-hungry”?
The answer is in the
GPU Architecture.
14. GPU vs CPU
GPU
● hundreds of simpler cores
CPU
● few very complex cores
● thousand of concurrent
hardware threads
● single-thread performance
optimization
● maximize floating-point
throughput
● transistor space dedicated
to complex ILP
● most die surface for
integer and fp units
● few die surface for integer
and fp units
24. Tegra X1 vs K1: power consumption
Architectural solutions to
improve energy efficiency:
● big.LITTLE processing
design
● Using of cluster migration
● Cache coherence solution
DRAM Energy efficiency
25. Conclusions
Power consumption reduction: current and future trends
involve both Hardware AND Software design
● Reduce data movement
● Lots of local processing in parallel
● Efficient caching and memory usage
● Where data lives
● Where computation happens, how it is scheduled
Energy efficiency must now be key metric.
