Ushering in a New Era: Argonne National Laboratory & Aurora
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Petaflops for the People
PETAFLOPS SPOTLIGHT: NERSC housands of researchers have used facilities of the Advanced T Scientific Computing Research (ASCR) program and its EXTREME-WEATHER Department of Energy (DOE) computing predecessors over the past four decades. Their studies of hurricanes, earthquakes, NUMBER-CRUNCHING green-energy technologies and many other basic and applied Certain problems lend themselves to solution by science problems have, in turn, benefited millions of people. computers. Take hurricanes, for instance: They’re They owe it mainly to the capacity provided by the National too big, too dangerous and perhaps too expensive Energy Research Scientific Computing Center (NERSC), the Oak to understand fully without a supercomputer. Ridge Leadership Computing Facility (OLCF) and the Argonne Leadership Computing Facility (ALCF). Using decades of global climate data in a grid comprised of 25-kilometer squares, researchers in These ASCR installations have helped train the advanced Berkeley Lab’s Computational Research Division scientific workforce of the future. Postdoctoral scientists, captured the formation of hurricanes and typhoons graduate students and early-career researchers have worked and the extreme waves that they generate. Those there, learning to configure the world’s most sophisticated same models, when run at resolutions of about supercomputers for their own various and wide-ranging projects. 100 kilometers, missed the tropical cyclones and Cutting-edge supercomputing, once the purview of a small resulting waves, up to 30 meters high. group of experts, has trickled down to the benefit of thousands of investigators in the broader scientific community. Their findings, published inGeophysical Research Letters, demonstrated the importance of running Today, NERSC, at Lawrence Berkeley National Laboratory; climate models at higher resolution. -
Fact Sheet: the Next Generation of Computing Has Arrived
News Fact Sheet The Next Generation of Computing Has Arrived: Performance to Power Amazing Experiences The new 5th Generation Intel® Core™ processor family is Intel’s latest wave of 14nm processors, delivering improved system and graphics performance, more natural and immersive user experiences, and enabling longer battery life compared to previous generations. The release of the 5th Generation Intel Core technology includes 14 new processors for consumers and businesses, including 10 new 15W processors with Intel® HD Graphics and four new 28W products with Intel® Iris™ Graphics. The 5th Generation Intel Core processor is purpose-built for the next generation of compute devices offering a thinner, lighter and more efficient experience across diverse form factors, including traditional notebooks, 2 in 1s, Ultrabooks™, Chromebooks, all-in-one desktop PCs and mini PCs. With the 5th Generation Intel Core processor availability, the “Broadwell” microarchitecture is expected to be the fastest mobile transition in company history to offer consumers a broad selection and availability of devices. Intel also started shipping its next generation 14nm processor for tablets, codenamed “Cherry Trail”, to device manufacturers. The new system on a chip (SoC) offers 64-bit computing, improved graphics with Intel® Generation 8-LP graphics, great performance and battery life for mainstream tablets. The platform offers world-class modem capabilities with LTE-Advanced on Intel® XMM™ 726x platform, which supports Cat-6 speeds and carrier aggregation. Customers will introduce new products based on this platform starting in the first half of this year. Key benefits of the 5th Generation Intel Core family and the next-generation 14nm processor for tablets include: Powerful Performance. -
1 Intel CEO Remarks Pat Gelsinger Q2'21 Earnings Webcast July 22
Intel CEO Remarks Pat Gelsinger Q2’21 Earnings Webcast July 22, 2021 Good afternoon, everyone. Thanks for joining our second-quarter earnings call. It’s a thrilling time for both the semiconductor industry and for Intel. We're seeing unprecedented demand as the digitization of everything is accelerated by the superpowers of AI, pervasive connectivity, cloud-to-edge infrastructure and increasingly ubiquitous compute. Our depth and breadth of software, silicon and platforms, and packaging and process, combined with our at-scale manufacturing, uniquely positions Intel to capitalize on this vast growth opportunity. Our Q2 results, which exceeded our top and bottom line expectations, reflect the strength of the industry, the demand for our products, as well as the superb execution of our factory network. As I’ve said before, we are only in the early innings of what is likely to be a decade of sustained growth across the industry. Our momentum is building as once again we beat expectations and raise our full-year revenue and EPS guidance. Since laying out our IDM 2.0 strategy in March, we feel increasingly confident that we're moving the company forward toward our goal of delivering leadership products in every category in which we compete. While we have work to do, we are making strides to renew our execution machine: 7nm is progressing very well. We’ve launched new innovative products, established Intel Foundry Services, and made operational and organizational changes to lay the foundation needed to win in the next phase of our company’s great history. Here at Intel, we’re proud of our past, pragmatic about the work ahead, but, most importantly, confident in our future. -
Intel 2019 Year Book
YEARBOOK 2019 POWERING THE FUTURE Our 2019 yearbook invites you to look back and reflect on a memorable year for Intel. TABLE OF CONTENTS 2019 kicked off with the announcement of our new p4 New CEO. Evolving culture. Expanded ambitions. chief executive, Bob Swan. It was followed by a stream of notable news: product announcements, technology p6 More data. More storage. More processing. breakthroughs, new customers and partnerships, p10 Innovation for the PC user experience and important moves to evolve Intel’s culture as the company entered its sixth decade. p12 Self-driving cars hit the road p2 p16 AI unlocks the power of data It’s a privilege to tell the Intel story in all its complexity and humanity. Looking through these pages, the p18 Helping customers push boundaries breadth and depth of what we’ve achieved in 12 p22 More supply to meet strong demand months is substantial, as is the strong foundation we’ve built for even greater impact in the future. p26 Next-gen hardware and software to unlock it p28 Tech’s future: Inventing and investing I hope you enjoy this colorful look at what’s possible when more than 100,000 individuals from every p32 Reinforcing the nature of Moore’s Law corner of the globe unite to change the world – p34 Building for the smarter future through technologies that make a positive difference to our customers, to society, and to people’s lives. — Claire Dixon, Chief Communications Officer NEW CEO. EVOLVING CULTURE. EXPANDED AMBITIONS. 2019 was an important year in Intel’s transformation, with a new chief executive officer, ambitious business priorities, an aspirational culture evolution, and a farewell to Focal. -
DARC: Design and Evaluation of an I/O Controller for Data Protection
DARC: Design and Evaluation of an I/O Controller for Data Protection ∗ ∗ Markos Fountoulakis , Manolis Marazakis, Michail D. Flouris, and Angelos Bilas Institute of Computer Science (ICS) Foundation for Research and Technology - Hellas (FORTH) N. Plastira 100, Vassilika Vouton, Heraklion, GR-70013, Greece {mfundul,maraz,flouris,bilas}@ics.forth.gr ABSTRACT tualization, versioning, data protection, error detection, I/O Lately, with increasing disk capacities, there is increased performance concern about protection from data errors, beyond masking of device failures. In this paper, we present a prototype I/O 1. INTRODUCTION stack for storage controllers that encompasses two data pro- tection features: (a) persistent checksums to protect data at- In the last three decades there has been a dramatic in- rest from silent errors and (b) block-level versioning to allow crease of storage density in magnetic and optical media, protection from user errors. Although these techniques have which has led to significantly lower cost per capacity unit. been previously used either at the device level (checksums) Today, most I/O stacks already encompass RAID features or at the host (versioning), in this work we implement these for protecting from device failures. However, recent stud- features in the storage controller, which allows us to use ies of large magnetic disk populations indicate that there any type of storage devices as well as any type of host I/O is also a significant failure rate of hardware and software stack. The main challenge in our approach is to deal with components in the I/O path, many of which are silent until persistent metadata in the controller I/O path. -
Logsafe: Secure and Scalable Data Logger for Iot Devices
University of Pennsylvania ScholarlyCommons Departmental Papers (CIS) Department of Computer & Information Science 4-2018 LogSafe: Secure and Scalable Data Logger for IoT Devices Hung Nguyen University of Pennsylvania, [email protected] Radoslav Ivanov University of Pennsylvania, [email protected] Linh T.X. Phan University of Pennsylvania, [email protected] Oleg Sokolsky University of Pennsylvania, [email protected] James Weimer University of Pennsylvania, [email protected] See next page for additional authors Follow this and additional works at: https://repository.upenn.edu/cis_papers Part of the Computer Engineering Commons, and the Computer Sciences Commons Recommended Citation Hung Nguyen, Radoslav Ivanov, Linh T.X. Phan, Oleg Sokolsky, James Weimer, and Insup Lee, "LogSafe: Secure and Scalable Data Logger for IoT Devices", The 3rd ACM/IEEE International Conference on Internet of Things Design and Implementation (IoTDI 2018) . April 2018. The 3rd ACM/IEEE International Conference on Internet of Things Design and Implementation (IoTDI 2018), Orlando, FL, USA April 17-20, 2018 This paper is posted at ScholarlyCommons. https://repository.upenn.edu/cis_papers/834 For more information, please contact [email protected]. LogSafe: Secure and Scalable Data Logger for IoT Devices Abstract As devices in the Internet of Things (IoT) increase in number and integrate with everyday lives, large amounts of personal information will be generated. With multiple discovered vulnerabilities in current IoT networks, a malicious attacker might be able to get access to and misuse this personal data. Thus, a logger that stores this information securely would make it possible to perform forensic analysis in case of such attacks that target valuable data. -
Semiconductor Industry Merger and Acquisition Activity from an Intellectual Property and Technology Maturity Perspective
Semiconductor Industry Merger and Acquisition Activity from an Intellectual Property and Technology Maturity Perspective by James T. Pennington B.S. Mechanical Engineering (2011) University of Pittsburgh Submitted to the System Design and Management Program in Partial Fulfillment of the Requirements for the Degree of Master of Science in Engineering and Management at the Massachusetts Institute of Technology September 2020 © 2020 James T. Pennington All rights reserved The author hereby grants to MIT permission to reproduce and to distribute publicly paper and electronic copies of this thesis document in whole or in part in any medium now known or hereafter created. Signature of Author ____________________________________________________________________ System Design and Management Program August 7, 2020 Certified by __________________________________________________________________________ Bruce G. Cameron Thesis Supervisor System Architecture Group Director in System Design and Management Accepted by __________________________________________________________________________ Joan Rubin Executive Director, System Design & Management Program THIS PAGE INTENTIALLY LEFT BLANK 2 Semiconductor Industry Merger and Acquisition Activity from an Intellectual Property and Technology Maturity Perspective by James T. Pennington Submitted to the System Design and Management Program on August 7, 2020 in Partial Fulfillment of the Requirements for the Degree of Master of Science in System Design and Management ABSTRACT A major method of acquiring the rights to technology is through the procurement of intellectual property (IP), which allow companies to both extend their technological advantage while denying it to others. Public databases such as the United States Patent and Trademark Office (USPTO) track this exchange of technology rights. Thus, IP can be used as a public measure of value accumulation in the form of technology rights. -
Architectural Trade-Offs in a Latency Tolerant Gallium Arsenide Microprocessor
Architectural Trade-offs in a Latency Tolerant Gallium Arsenide Microprocessor by Michael D. Upton A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy (Electrical Engineering) in The University of Michigan 1996 Doctoral Committee: Associate Professor Richard B. Brown, CoChairperson Professor Trevor N. Mudge, CoChairperson Associate Professor Myron Campbell Professor Edward S. Davidson Professor Yale N. Patt © Michael D. Upton 1996 All Rights Reserved DEDICATION To Kelly, Without whose support this work may not have been started, would not have been enjoyed, and could not have been completed. Thank you for your continual support and encouragement. ii ACKNOWLEDGEMENTS Many people, both at Michigan and elsewhere, were instrumental in the completion of this work. I would like to thank my co-chairs, Richard Brown and Trevor Mudge, first for attracting me to Michigan, and then for allowing our group the freedom to explore many different ideas in architecture and circuit design. Their guidance and motivation combined to make this a truly memorable experience. I am also grateful to each of my other dissertation committee members: Ed Davidson, Yale Patt, and Myron Campbell. The support and encouragement of the other faculty on the project, Karem Sakallah and Ron Lomax, is also gratefully acknowledged. My friends and former colleagues Mark Rossman, Steve Sugiyama, Ray Farbarik, Tom Rossman and Kendall Russell were always willing to lend their assistance. Richard Oettel continually reminded me of the valuable support of friends and family, and the importance of having fun in your work. Our corporate sponsors: Cascade Design Automation, Chronologic, Cadence, and Metasoft, provided software and support that made this work possible. -
Roofline Model Toolkit: a Practical Tool for Architectural and Program
Roofline Model Toolkit: A Practical Tool for Architectural and Program Analysis Yu Jung Lo, Samuel Williams, Brian Van Straalen, Terry J. Ligocki, Matthew J. Cordery, Nicholas J. Wright, Mary W. Hall, and Leonid Oliker University of Utah, Lawerence Berkeley National Laboratory {yujunglo,mhall}@cs.utah.edu {swwilliams,bvstraalen,tjligocki,mjcordery,njwright,loliker}@lbl.gov Abstract. We present preliminary results of the Roofline Toolkit for multicore, manycore, and accelerated architectures. This paper focuses on the processor architecture characterization engine, a collection of portable instrumented micro benchmarks implemented with Message Passing Interface (MPI), and OpenMP used to express thread-level paral- lelism. These benchmarks are specialized to quantify the behavior of dif- ferent architectural features. Compared to previous work on performance characterization, these microbenchmarks focus on capturing the perfor- mance of each level of the memory hierarchy, along with thread-level parallelism, instruction-level parallelism and explicit SIMD parallelism, measured in the context of the compilers and run-time environments. We also measure sustained PCIe throughput with four GPU memory managed mechanisms. By combining results from the architecture char- acterization with the Roofline model based solely on architectural spec- ifications, this work offers insights for performance prediction of current and future architectures and their software systems. To that end, we in- strument three applications and plot their resultant performance on the corresponding Roofline model when run on a Blue Gene/Q architecture. Keywords: Roofline, Memory Bandwidth, CUDA Unified Memory 1 Introduction The growing complexity of high-performance computing architectures makes it difficult for users to achieve sustained application performance across different architectures. -
TOP500 Supercomputer Sites
7/24/2018 News | TOP500 Supercomputer Sites HOME | SEARCH | REGISTER RSS | MY ACCOUNT | EMBED RSS | SUPER RSS | Contact Us | News | TOP500 Supercomputer Sites http://top500.org/blog/category/feature-article/feeds/rss Are you the publisher? Claim or contact Browsing the Latest Browse All Articles (217 Live us about this channel Snapshot Articles) Browser Embed this Channel Description: content in your HTML TOP500 News Search Report adult content: 04/27/18--03:14: UK Commits a 0 0 Billion Pounds to AI Development click to rate The British government and the private sector are investing close to £1 billion Account: (login) pounds to boost the country’s artificial intelligence sector. The investment, which was announced on Thursday, is part of a wide-ranging strategy to make the UK a global leader in AI and big data. More Channels Under the investment, known as the “AI Sector Deal,” government, industry, and academia will contribute £603 million in new funding, adding to the £342 million already allocated in existing budgets. That brings the grand total to Showcase £945 million, or about $1.3 billion at the current exchange rate. The UK RSS Channel Showcase 1586818 government is also looking to increase R&D spending across all disciplines by 2.4 percent, while also raising the R&D tax credit from 11 to 12 percent. This is RSS Channel Showcase 2022206 part of a broader commitment to raise government spending in this area from RSS Channel Showcase 8083573 around £9.5 billion in 2016 to £12.5 billion in 2021. RSS Channel Showcase 1992889 The UK government policy paper that describes the sector deal meanders quite a bit, describing a lot of programs and initiatives that intersect with the AI investments, but are otherwise free-standing. -
MPI on Aurora
AN OVERVIEW OF AURORA, ARGONNE’S UPCOMING EXASCALE SYSTEM ALCF DEVELOPERS SESSION COLLEEN BERTONI, SUDHEER CHUNDURI www.anl.gov AURORA: An Intel-Cray System Intel/Cray machine arriving at Argonne in 2021 Sustained Performance greater than 1 Exaflops 2 AURORA: A High-level View § Hardware Architecture: § Intel Xeon processors and Intel Xe GPUs § Greater than 10 PB of total memory § Cray Slingshot network and Shasta platform § IO • Uses Lustre and Distributed Asynchronous Object Store IO (DAOS) • Greater than 230 PB of storage capacity and 25 TB/s of bandwidth § Software (Intel One API umbrella): § Intel compilers (C,C++,Fortran) § Programming models: DPC++, OpenMP, OpenCL § Libraries: oneMKL, oneDNN, oneDAL § Tools: VTune, Advisor § Python 3 Node-level Hardware The Evolution of Intel GPUs Source: Intel 5 Intel GPUs § Intel Integrated GPUs are used for over a decade in § Laptops (e.g. MacBook pro) § Desktops § Servers § Recent and upcoming integrated generations : § Gen 9 – used in Skylake based nodes § Gen 11 – used in Ice Lake based nodes § Gen 9: Double precision peak performance: 100-300 GF § Low by design due to power and space limits Layout of Architecture components for an Intel Core i7 processor 6700K for desktop systems (91 W TDP, 122 mm) § Future Intel Xe (Gen 12) GPU series will provide both integrated and discrete GPUs 6 Intel GPU Building Blocks EU: Execution Unit Subslice L2 Slice: 24 EUs SIMD FPU Dispatch&I$ L1 Shared Local Memory (64 KB/subslice) SIMD FPU Subslice: 8 EUs Send 8x EU Sampler L2 $ L3 Data Cache Branch Dataport -
Characterizing and Understanding HPC Job Failures Over the 2K-Day Life of IBM Bluegene/Q System
Characterizing and Understanding HPC Job Failures over The 2K-day Life of IBM BlueGene/Q System Sheng Di,∗ Hanqi Guo,∗ Eric Pershey,∗ Marc Snir,y Franck Cappello∗y ∗Argonne National Laboratory, IL, USA [email protected], [email protected], [email protected], [email protected] yUniversity of Illinois at Urbana-Champaign, IL, USA [email protected] Abstract—An in-depth understanding of the failure features of Blue Joule (UK), also adopt the same Blue Gene/Q system HPC jobs in a supercomputer is critical to the large-scale system architecture and they are still in operation. maintenance and improvement of the service quality for users. In Studying the job failure features in a large-scale system is this paper, we investigate the features of hundreds of thousands of jobs in one of the most powerful supercomputers, the IBM nontrivial in that it involves numerous messages logged from Blue Gene/Q Mira, based on 2001 days of observations with a across multiple data sources and many messages are heavily total of over 32.44 billion core-hours. We study the impact of the duplicated [2]. In our work, we performed a joint analysis system’s events on the jobs’ execution in order to understand the by leveraging four different data sources: the reliability, avail- system’s reliability from the perspective of jobs and users. The ability, and serviceability (RAS) log; task execution log; job characterization involves a joint analysis based on multiple data sources, including the reliability, availability, and serviceability scheduling log; and I/O behavior log. The RAS log is the most (RAS) log; job scheduling log; the log regarding each job’s important system log related to system reliability such as node physical execution tasks; and the I/O behavior log.