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Penguin Computing Upgrades Corona with Latest AMD Radeon Instinct GPU Technology for Enhanced ML and AI Capabilities
Penguin Computing Upgrades Corona with latest AMD Radeon Instinct GPU Technology for Enhanced ML and AI Capabilities November 18, 2019 Fremont, CA., November 18, 2019 -Penguin Computing, a leader in high-performance computing (HPC), artificial intelligence (AI), and enterprise data center solutions and services, today announced that Corona, an HPC cluster first delivered to Lawrence Livermore National Lab (LLNL) in late 2018, has been upgraded with the newest AMD Radeon Instinct™ MI60 accelerators, based on Vega which, per AMD, is the World’s 1st 7nm GPU architecture that brings PCIe® 4.0 support. This upgrade is the latest example of Penguin Computing and LLNL’s ongoing collaboration aimed at providing additional capabilities to the LLNL user community. As previously released, the cluster consists of 170 two-socket nodes with 24-core AMD EPYCTM 7401 processors and a PCIe 1.6 Terabyte (TB) nonvolatile (solid-state) memory device. Each Corona compute node is GPU-ready with half of those nodes today utilizing four AMD Radeon Instinct MI25 accelerators per node, delivering 4.2 petaFLOPS of FP32 peak performance. With the MI60 upgrade, the cluster increases its potential PFLOPS peak performance to 9.45 petaFLOPS of FP32 peak performance. This brings significantly greater performance and AI capabilities to the research communities. “The Penguin Computing DOE team continues our collaborative venture with our vendor partners AMD and Mellanox to ensure the Livermore Corona GPU enhancements expand the capabilities to continue their mission outreach within various machine learning communities,” said Ken Gudenrath, Director of Federal Systems at Penguin Computing. Corona is being made available to industry through LLNL’s High Performance Computing Innovation Center (HPCIC). -
List of Brands
Global Consumer 2019 List of Brands Table of Contents 1. Digital music 2 2. Video-on-Demand 4 3. Video game stores 7 4. Digital video games shops 11 5. Video game streaming services 13 6. Book stores 15 7. eBook shops 19 8. Daily newspapers 22 9. Online newspapers 26 10. Magazines & weekly newspapers 30 11. Online magazines 34 12. Smartphones 38 13. Mobile carriers 39 14. Internet providers 42 15. Cable & satellite TV provider 46 16. Refrigerators 49 17. Washing machines 51 18. TVs 53 19. Speakers 55 20. Headphones 57 21. Laptops 59 22. Tablets 61 23. Desktop PC 63 24. Smart home 65 25. Smart speaker 67 26. Wearables 68 27. Fitness and health apps 70 28. Messenger services 73 29. Social networks 75 30. eCommerce 77 31. Search Engines 81 32. Online hotels & accommodation 82 33. Online flight portals 85 34. Airlines 88 35. Online package holiday portals 91 36. Online car rental provider 94 37. Online car sharing 96 38. Online ride sharing 98 39. Grocery stores 100 40. Banks 104 41. Online payment 108 42. Mobile payment 111 43. Liability insurance 114 44. Online dating services 117 45. Online event ticket provider 119 46. Food & restaurant delivery 122 47. Grocery delivery 125 48. Car Makes 129 Statista GmbH Johannes-Brahms-Platz 1 20355 Hamburg Tel. +49 40 2848 41 0 Fax +49 40 2848 41 999 [email protected] www.statista.com Steuernummer: 48/760/00518 Amtsgericht Köln: HRB 87129 Geschäftsführung: Dr. Friedrich Schwandt, Tim Kröger Commerzbank AG IBAN: DE60 2004 0000 0631 5915 00 BIC: COBADEFFXXX Umsatzsteuer-ID: DE 258551386 1. -
Survey and Benchmarking of Machine Learning Accelerators
1 Survey and Benchmarking of Machine Learning Accelerators Albert Reuther, Peter Michaleas, Michael Jones, Vijay Gadepally, Siddharth Samsi, and Jeremy Kepner MIT Lincoln Laboratory Supercomputing Center Lexington, MA, USA freuther,pmichaleas,michael.jones,vijayg,sid,[email protected] Abstract—Advances in multicore processors and accelerators components play a major role in the success or failure of an have opened the flood gates to greater exploration and application AI system. of machine learning techniques to a variety of applications. These advances, along with breakdowns of several trends including Moore’s Law, have prompted an explosion of processors and accelerators that promise even greater computational and ma- chine learning capabilities. These processors and accelerators are coming in many forms, from CPUs and GPUs to ASICs, FPGAs, and dataflow accelerators. This paper surveys the current state of these processors and accelerators that have been publicly announced with performance and power consumption numbers. The performance and power values are plotted on a scatter graph and a number of dimensions and observations from the trends on this plot are discussed and analyzed. For instance, there are interesting trends in the plot regarding power consumption, numerical precision, and inference versus training. We then select and benchmark two commercially- available low size, weight, and power (SWaP) accelerators as these processors are the most interesting for embedded and Fig. 1. Canonical AI architecture consists of sensors, data conditioning, mobile machine learning inference applications that are most algorithms, modern computing, robust AI, human-machine teaming, and users (missions). Each step is critical in developing end-to-end AI applications and applicable to the DoD and other SWaP constrained users. -
Electronic 3D Models Catalogue (On July 26, 2019)
Electronic 3D models Catalogue (on July 26, 2019) Acer 001 Acer Iconia Tab A510 002 Acer Liquid Z5 003 Acer Liquid S2 Red 004 Acer Liquid S2 Black 005 Acer Iconia Tab A3 White 006 Acer Iconia Tab A1-810 White 007 Acer Iconia W4 008 Acer Liquid E3 Black 009 Acer Liquid E3 Silver 010 Acer Iconia B1-720 Iron Gray 011 Acer Iconia B1-720 Red 012 Acer Iconia B1-720 White 013 Acer Liquid Z3 Rock Black 014 Acer Liquid Z3 Classic White 015 Acer Iconia One 7 B1-730 Black 016 Acer Iconia One 7 B1-730 Red 017 Acer Iconia One 7 B1-730 Yellow 018 Acer Iconia One 7 B1-730 Green 019 Acer Iconia One 7 B1-730 Pink 020 Acer Iconia One 7 B1-730 Orange 021 Acer Iconia One 7 B1-730 Purple 022 Acer Iconia One 7 B1-730 White 023 Acer Iconia One 7 B1-730 Blue 024 Acer Iconia One 7 B1-730 Cyan 025 Acer Aspire Switch 10 026 Acer Iconia Tab A1-810 Red 027 Acer Iconia Tab A1-810 Black 028 Acer Iconia A1-830 White 029 Acer Liquid Z4 White 030 Acer Liquid Z4 Black 031 Acer Liquid Z200 Essential White 032 Acer Liquid Z200 Titanium Black 033 Acer Liquid Z200 Fragrant Pink 034 Acer Liquid Z200 Sky Blue 035 Acer Liquid Z200 Sunshine Yellow 036 Acer Liquid Jade Black 037 Acer Liquid Jade Green 038 Acer Liquid Jade White 039 Acer Liquid Z500 Sandy Silver 040 Acer Liquid Z500 Aquamarine Green 041 Acer Liquid Z500 Titanium Black 042 Acer Iconia Tab 7 (A1-713) 043 Acer Iconia Tab 7 (A1-713HD) 044 Acer Liquid E700 Burgundy Red 045 Acer Liquid E700 Titan Black 046 Acer Iconia Tab 8 047 Acer Liquid X1 Graphite Black 048 Acer Liquid X1 Wine Red 049 Acer Iconia Tab 8 W 050 Acer -
Videocard Benchmarks
Software Hardware Benchmarks Services Store Support About Us Forums 0 CPU Benchmarks Video Card Benchmarks Hard Drive Benchmarks RAM PC Systems Android iOS / iPhone Videocard Benchmarks Over 1,000,000 Video Cards Benchmarked Video Card List Below is an alphabetical list of all Video Card types that appear in the charts. Clicking on a specific Video Card will take you to the chart it appears in and will highlight it for you. Find Videocard VIDEO CARD Single Video Card Passmark G3D Rank Videocard Value Price Videocard Name Mark (lower is better) (higher is better) (USD) High End (higher is better) 3DP Edition 826 822 NA NA High Mid Range Low Mid Range 9xx Soldiers sans frontiers Sigma 2 21 1926 NA NA Low End 15FF 8229 114 NA NA 64MB DDR GeForce3 Ti 200 5 2004 NA NA Best Value Common 64MB GeForce2 MX with TV Out 2 2103 NA NA Market Share (30 Days) 128 DDR Radeon 9700 TX w/TV-Out 44 1825 NA NA 128 DDR Radeon 9800 Pro 62 1768 NA NA 0 Compare 128MB DDR Radeon 9800 Pro 66 1757 NA NA 128MB RADEON X600 SE 49 1809 NA NA Video Card Mega List 256MB DDR Radeon 9800 XT 37 1853 NA NA Search Model 256MB RADEON X600 67 1751 NA NA GPU Compute 7900 MOD - Radeon HD 6520G 610 1040 NA NA Video Card Chart 7900 MOD - Radeon HD 6550D 892 775 NA NA A6 Micro-6500T Quad-Core APU with RadeonR4 220 1421 NA NA A10-8700P 513 1150 NA NA ABIT Siluro T400 3 2059 NA NA ALL-IN-WONDER 9000 4 2024 NA NA ALL-IN-WONDER 9800 23 1918 NA NA ALL-IN-WONDER RADEON 8500DV 5 2009 NA NA ALL-IN-WONDER X800 GT 84 1686 NA NA All-in-Wonder X1800XL 30 1889 NA NA All-in-Wonder X1900 127 1552 -
AI Chips: What They Are and Why They Matter
APRIL 2020 AI Chips: What They Are and Why They Matter An AI Chips Reference AUTHORS Saif M. Khan Alexander Mann Table of Contents Introduction and Summary 3 The Laws of Chip Innovation 7 Transistor Shrinkage: Moore’s Law 7 Efficiency and Speed Improvements 8 Increasing Transistor Density Unlocks Improved Designs for Efficiency and Speed 9 Transistor Design is Reaching Fundamental Size Limits 10 The Slowing of Moore’s Law and the Decline of General-Purpose Chips 10 The Economies of Scale of General-Purpose Chips 10 Costs are Increasing Faster than the Semiconductor Market 11 The Semiconductor Industry’s Growth Rate is Unlikely to Increase 14 Chip Improvements as Moore’s Law Slows 15 Transistor Improvements Continue, but are Slowing 16 Improved Transistor Density Enables Specialization 18 The AI Chip Zoo 19 AI Chip Types 20 AI Chip Benchmarks 22 The Value of State-of-the-Art AI Chips 23 The Efficiency of State-of-the-Art AI Chips Translates into Cost-Effectiveness 23 Compute-Intensive AI Algorithms are Bottlenecked by Chip Costs and Speed 26 U.S. and Chinese AI Chips and Implications for National Competitiveness 27 Appendix A: Basics of Semiconductors and Chips 31 Appendix B: How AI Chips Work 33 Parallel Computing 33 Low-Precision Computing 34 Memory Optimization 35 Domain-Specific Languages 36 Appendix C: AI Chip Benchmarking Studies 37 Appendix D: Chip Economics Model 39 Chip Transistor Density, Design Costs, and Energy Costs 40 Foundry, Assembly, Test and Packaging Costs 41 Acknowledgments 44 Center for Security and Emerging Technology | 2 Introduction and Summary Artificial intelligence will play an important role in national and international security in the years to come. -
Tech Trends 2017: the Kinetic Enterprise
DIGITAL ANALYTICS CYBER Asset User Wireless Information Information Cyber intelligence engagement and mobility management automation security User Applied Real Cyber Social engagement mobility Visualization analytics intelligence computing User Enterprise Geospatial Big data Digital Gamification Social business empowerment mobility visualization goes to work identities unleashed Gamification Social Finding No such goes to work reengineering Mobile only the face of thing as by design (and beyond) your data hacker-proof Industrialized Digital Cognitive crowdsourcing Social engagement Wearables analytics Cyber security activation Dimensional Ambient Amplified Cyber marketing computing intelligence implications AR and VR Internet Industrialized Blockchain: go to work of Things analytics Democratized trust Machine Dark Blockchain: Mixed reality intelligence analytics Trust economy 2010 2011 2012 2013 2014 2015 2016 2017 Trending the trends: Eight years of research Exponentials IT Inevitable Everything- watch list unbounded architecture as-a-service Social impact of Right- Autonomic Reimagining exponentials speed IT platforms core systems CIO as chief Software- Exponentials IT worker of integration defined API Core the future officer everything economy renaissance Exponentials CIO as venture Real-time Cloud In-memory Technical capitalist DevOps orchestration revolution debt reversal Design as Business CIO as IPv6 (and Reinventing a discipline of IT postdigital this time we the ERP catalyst mean it) engine Measured Hyper-hybrid Outside-in innovation -
Ece Connections
ECE2019/2020 CONNECTIONS BUILDING THE NEW COMPUTER USING REVOLUTIONARY NEW ARCHITECTURES Page 16 ECE CONNECTIONS DIRECTOR’S REFLECTIONS: ALYSSA APSEL Wishna Robyn s I write this, our Cornell scaling alone isn’t the answer to more community is adapting powerful and more efficient computers. to the rapidly evolving We can build chips with upwards of four conditions resulting from billion transistors in a square centimeter the COVID-19 pandemic. (such as Apple’s A11 chip), but when My heart is heavy with attempting to make devices any smaller the distress, uncertainty and anxiety this the electrical properties become difficult to Abrings for so many of us, and in particular control. Pushing them faster also bumps seniors who were looking forward to their up against thermal issues as the predicted last semesters at Cornell. temperatures on-chip become comparable I recognize that these are difficult to that of a rocket nozzle. times and many uncertainties remain, Does that mean the end of innovation very nature of computation by building but I sincerely believe that by working in electronics? No, it’s just the beginning. memory devices, algorithms, circuits, and together as a community, we will achieve Instead of investing in manufacturing devices that directly integrate computation the best possible results for the health and that matches the pace of Moore’s law, even at the cellular level. The work well-being of all of Cornell. Although we major manufacturers have realized highlighted in this issue is exciting in that are distant from each other, our work in that it is cost effective to pursue other it breaks the traditional separation between ECE continues. -
Final Project Milestone APA Format
Running head: FINAL PROJECT MILESTONE ONE 1 FINAL PROJECT MILESTONE ONE [Author] [Institution] FINAL PROJECT MILESTONE ONE 2 Essay Technology is basically an application of scientific knowledge which is utilized for practical purposes, more likely in industry. Moreover, it can be referred to as the use of tools, machines, techniques, material and power sources for making the work in an easier and productive manner. Generally, science is concerned with the understanding on how and why things happen, whereas, technology deals with making things happen. The world in today’s life is surrounded with technologies. In every aspect of human lives, technology is making their work easier and in a productive way (Abroms & Phillips, 2011). Although, there are various disadvantages of these technologies but the advantages are always more. Whenever, someone hears the word technology, the first company which comes into their mind is Apple Inc. This is a firm which has brought enormous change in the world by introducing their iPhones and other i products. The company has changed the entire thought process of the humans. Apple Inc. is an American multinational technological corporation which is headquartered in Cupertino, California. The firm designs, develops and sells the consumer electronics products, computer software products and many other online services. Moreover, the hardware product of the firm includes iPhone smartphone, iPad Tablet computer, Mac personal computer, iPod portable media player, Apple smart watch, Apple TV and HomePod smart speaker. Software products include the macOS and iOS operating system, iTunes media player and many more. This firm was founded by Steve Jobs, Steve Wozniak and Ronald Wayne in 1976 and it was incorporated as Apple Computer, Inc. -
June 2017 Welcome to the Idevices (Iphone, Ipad, Apple Watch & Ipod) SIG Meeting
June 2017 Welcome to the iDevices (iPhone, iPad, Apple Watch & iPod) SIG Meeting. To find Apps that are free for a short time, click these icons below: http://www.iosnoops.com/iphone-ipad- apps-gone-free/ http://appsliced.co/apps Important Note: I have been conducting the iDevice SIG for 6-1/2 years. It is time for me to pass along the hosting of this SIG to someone else. Thank you, everyone, for of your attendance and support. Phil Pensabene will take over the iDevice SIG beginning in July. Thank you, Phil. Click HERE to see the Keynote Address Apple just changed its storage plan options ... again Tuesday, Jun 6, 2017 at 8:08 pm EDT Apple updated its iCloud storage plan again. The good news is that it'll cost you a lot less to get a lot more! If you've been thinking about upgrading (or downgrading) your iCloud storage plan, you're in luck. Apple has just made some changes to its iCloud storage plan that will probably make you happy. Apple has dropped the 1TB storage tier from the iCloud lineup. But have no fear 1TB subscribers! Apple also dropped the price of 2TB of storage by half the price. All former 1TB subscribers will be automatically upgraded to the 2TB plan without any extra cost. All 2TB subscribers will now only pay $9.99 per month for all the storage you can handle! The new tier structure is as follows: 5GB - Free 50GB - $0.99 200GB - $2.99 2TB - $9.99 If you're still not sure which plan is right for you, we've got a useful little guide to help you out. -
Apple A11 Bionic
Apple A11 The Apple A11 Bionic is a 64-bit ARM-based system on a chip (SoC), designed by Apple Inc.[6] and manufactured by TSMC.[1] It first appeared in the iPhone 8, iPhone 8 Plus, and iPhone Apple A11 Bionic X which were introduced on September 12, 2017.[6] It has two high-performance cores which are 25% faster than the Apple A10 and four high-efficiency cores which are up to 70% faster than the energy-efficient cores in the A10.[6][7] Contents Design Neural Engine Products that include the Apple A11 Bionic See also References Produced From Design September 12, 2017 to [1][6][4] The A11 features an Apple-designed 64-bit ARMv8-A six-core CPU, with two high-performance cores at 2.39 GHz, called Monsoon, and four energy-efficient cores, called Mistral. present The A11 uses a new second-generation performance controller, which permits the A11 to use all six cores simultaneously,[8] unlike its predecessor the A10. The A11 also integrates an Apple- Designed by Apple Inc. designed three-core graphics processing unit (GPU) with 30% faster graphics performance than the A10.[6] Embedded in the A11 is the M11 motion coprocessor.[9] The A11 includes a new Common [1] image processor which supports computational photography functions such as lighting estimation, wide color capture, and advanced pixel processing.[6] TSMC manufacturer(s) [1] [7] 2 [10] The A11 is manufactured by TSMC using a 10 nm FinFET process and contains 4.3 billion transistors on a die 87.66 mm in size, 30% smaller than the A10. -
Ecodesign Preparatory Study on Mobile Phones, Smartphones and Tablets
Ecodesign preparatory study on mobile phones, smartphones and tablets Draft Task 4 Report Technologies Written by Fraunhofer IZM, Fraunhofer ISI, VITO October – 2020 Authors: Karsten Schischke (Fraunhofer IZM) Christian Clemm (Fraunhofer IZM) Anton Berwald (Fraunhofer IZM) Marina Proske (Fraunhofer IZM) Gergana Dimitrova (Fraunhofer IZM) Julia Reinhold (Fraunhofer IZM) Carolin Prewitz (Fraunhofer IZM) Christoph Neef (Fraunhofer ISI) Contributors: Antoine Durand (Quality control, Fraunhofer ISI) Clemens Rohde (Quality control, Fraunhofer ISI) Simon Hirzel (Quality control, Fraunhofer ISI) Mihaela Thuring (Quality control, contract management, VITO) Study website: https://www.ecosmartphones.info EUROPEAN COMMISSION Directorate-General for Internal Market, Industry, Entrepreneurship and SMEs Directorate C — Sustainable Industry and Mobility DDG1.C.1 — Circular Economy and Construction Contact: Davide Polverini E-mail: [email protected] European Commission B-1049 Brussels 2 Ecodesign preparatory study on mobile phones, smartphones and tablets Draft Task 4 Report Technologies 4 EUROPEAN COMMISSION Europe Direct is a service to help you find answers to your questions about the European Union. Freephone number (*): 00 800 6 7 8 9 10 11 (*) The information given is free, as are most calls (though some operators, phone boxes or hotels may charge you). LEGAL NOTICE This document has been prepared for the European Commission however it reflects the views only of the authors, and the Commission cannot be held responsible for any use which may be made of the information contained therein. More information on the European Union is available on the Internet (http://www.europa.eu). Luxembourg: Publications Office of the European Union, 2020 ISBN number doi:number © European Union, 2020 Reproduction is authorised provided the source is acknowledged.