14 Nov RESEARCH PAPER: Synthesis Modeling: The Intersection Of HPC And Machine Learning

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Historically, numerical analysis has formed the backbone of supercomputing for decades by applying mathematical models of first-principle physics to simulate the behavior of systems from subatomic to galactic scale. Recently, scientists have begun experimenting with a relatively new approach to understand complex systems using machine learning (ML) predictive models, primarily Deep Neural Networks (DNN), trained […]

27 Oct Amazon And NVIDIA Simplify Machine Learning

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NVIDIA and Amazon.com have announced new Machine Learning software stacks in the NVIDIA GPU Cloud (NGC), and a new 8 Volta GPU EC2 instance for immediate availability, respectively. While this announcement was completely expected, it is an important milestone along the road to simplifying and lowering the costs of Machine Learning development and deployment for AI […]

17 Oct Startup Accelize Simplifies FPGA Acceleration

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FPGAs have been the hot new topic in data center discussions, ever since Microsoft shared their FPGA successes at the HotChips conference in August. Xilinx  and Amazon Web Services continued to amp up the buzz by partnering with IP providers such as Edico Genome, Ryft Systems Inc., and NGCodec Inc., to deliver acceleration-as-a-service with Amazon […]

28 Sep NVIDIA Targets Next AI Frontiers: Inference And China

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NVIDIA’s meteoric growth in the datacenter, where its business is now generating some $1.6B annually, has been largely driven by the demand to train deep neural networks for Machine Learning (ML) and Artificial Intelligence (AI)—an area where the computational requirements are simply mindboggling. Much of this business is coming from the largest datacenters in the […]

27 Sep Amazon And Xilinx Deliver New FPGA Solutions

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Datacenter adoption of FPGAs for workload acceleration has been a hot topic of late—especially after Microsoft announced significant gains in its datacenter at the Hot Chips conference in August. However, due to the rare skillset these reconfigurable silicon platforms demand, widespread adoption has been slow to materialize outside of Microsoft . I believe that might […]

28 Aug Microsoft: FPGA Wins Versus Google TPUs For AI

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The Microsoft Brainwave mezzanine card extends each server with an Intel Altera Stratix 10 FPGA accelerator, synthesized to act as a “Soft DNN Processing Unit,” or DPU, and a fabric interconnect that enables datacenter-scale persistent neural networks. At the recent Hot Chips conference, three of the world’s largest datacenter companies detailed projects that exploit Field […]

04 Aug Will ASIC Chips Become The Next Big Thing In AI?

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When Google announced its second generation of ASICs to accelerate the company’s machine learning processing, my phone started ringing off the hook with questions about the potential impact on the semiconductor industry. Would the other members of the Super 7, the world’s largest datacenters, all rush to build their own chips for AI? How might […]

17 Jul Microsoft Finds Its AI Voice

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Microsoft held an intimate analyst and press event in London this week, coincident with the 20th anniversary of the founding of the Cambridge Research Lab, the European hub led by Professor Christopher Bishop. Microsoft now employs over 7,000 Artificial Intelligence (AI) research scientists and development engineers around the world under Microsoft Research (MSR) Executive VP […]

10 Jul Baidu Adds Momentum To NVIDIA’s Lead In AI

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It is not much of an exaggeration to say that Artificial Intelligence (AI), in its present form, would not be possible without NVIDIA GPUs. NVIDIA has enjoyed near-universal support from some of the largest adopters of Machine Learning technology, as NVIDIA’s speedy GPUs accelerate the training and use of the Deep Neural Networks that enable […]

26 Jun ISC17: HPC Embraces Diversity As AMD & ARM Up The Ante Vs. Intel, IBM And NVIDIA

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Renewed Competition in HPC Will Enable Workload Optimization Intel has enjoyed a dominant position in High Performance Computing (HPC) processors for nearly a decade now, with only IBM  POWER offering a viable CPU alternative, since Advanced Micro Deviceseffectively, albeit perhaps unintentionally, exited the market in 2010. Meanwhile, NVIDIA has kept things interesting by delivering GPUs as […]

22 May Google Cloud TPU: Strategic Implications For Google, NVIDIA And The Machine Learning Industry

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Google  announced the 2nd generation of the company’s TensorFlow Processing Unit (TPU), now called the Cloud TPU, at the annual Google I/O event, wowing the industry with performance for Machine Learning that appeared to eclipse NVIDIA’s Tesla Volta GPU only one week after that chip was launched. (See below why I say “appeared”.) Unlike Google’s […]

16 May RESEARCH BRIEF: AMD Lays The Foundations For Machine Learning With Radeon Vega Frontier & Optimized Software

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Advanced Micro Devices (AMD) has shared more details about its upcoming code-named “Vega” family of GPUs, as well as information regarding the progress the company has made with its open-source ROCm software stack for HPC and Machine Learning (ML). Investors and AI practitioners alike would like to see AMD enter this market as a second […]

16 May AMD Targets Machine Learning With New Radeon Vega Frontier & Optimized Software

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Advanced Micro Devices  (AMD) has shared more details about its upcoming Vega family of GPUs, as well as information regarding the progress the company has made with its open-source ROCm software stack for HPC and Machine Learning (ML). These new Vega GPUs look like they have sufficient performance to be in the same ballpark as […]

15 May Why NVIDIA Is Building Its Own TPU

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The blistering pace of innovation in artificial intelligence for image, voice, robotic and self-driving vehicle applications has been fueled, in large part, by NVIDIA’s GPU chips that deliver the massive compute power required by the underlying math required for Deep Learning. While NVIDIA continues to reap the benefits of its investments in GPUs, there has […]

11 May NVIDIA GPU Cloud: It’s Not What You May Think It Is

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NVIDIA made a slew of important announcements at its annual GPU conference today, including new hardware, new software and a new design win (Toyota) for self-driving cars. I will cover these announcements in a separate article. But one announcement in particular has created some confusion that I’d like to help clear up, and that’s the […]

13 Apr Google’s TPU For AI Is Really Fast, But Does It Matter?

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After nearly a year since the introduction of the Google TensorFlow Processing Unit, or TPU, Google has finally released detailed performance and power metrics for its in-house AI chip. The chip is impressive on many fronts, however Google understandably has no plans to sell it to its competitors, so its impact on the industry is debatable. […]

30 Mar Intel Touts Manufacturing & Technology Leadership: Moore’s Law Is Alive And Well

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For quite some time now, many chip industry watchers have questioned the future sustainability of Moore’s Law. Named after Intel founder Gordon Moore, this industry constant observes that semiconductor densities double every 2 years, and has underpinned the industry for 52 years. Recently, some have also begun to question whether Intel has lost its vaunted […]

24 Mar NVIDIA Scores Yet Another GPU Cloud For AI With Tencent

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NVIDIA’s speedy GPUs and Machine Learning software have unquestionably become the gold standard for building Artificial Intelligence (AI) applications. And today, NVIDIA added TenCent to their list of cloud service providers that offer access to NVIDIA hardware in their clouds for AI and other compute intensive applications. This marks a significant milestone in the global […]

17 Mar Why Intel Is Buying Mobileye, And What Does It Need To Do To Be Successful?

In a move that Intel hopes can propel it to the forefront of The Next Big Thing, Intel announced it would purchase Mobileye, an Israeli company that makes sensors and cameras for driverless vehicles. Buying a leader to become a leader is never cheap: Intel will pay $13.3B for the firm, a 34% premium over […]

03 Mar RESEARCH PAPER: A Machine Learning Application Landscape

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2016 was a strong year for Machine Learning (ML) and Artificial Intelligence (AI) with many high tech firms claiming that they are now an “AI Company”, notably Amazon, Baidu, Facebook, Google, IBM, Intel, Microsoft, NVIDIA, and Tesla. In 2017, the field will broaden to include AMD, Qualcomm, and Xilinx. Moor Insights & Strategy (MI&S) expects Machine Learning based AIs […]