NVIDIA Extends Lead on MLPerf Benchmark with A100 Delivering up to 237x Faster AI Inference Than CPUs, Enabling Businesses to Move AI from Research to Production SANTA CLARA, Calif., Oct. 21, 2020 (GLOBE NEWSWIRE) -- NVIDIA today announced its AI computing platform has again smashed performance records in the latest round of MLPerf, extending its lead on the industry’s only independent benchmark measuring AI performance of hardware, software and services.NVIDIA won every test across all six application areas for data center and edge computing systems in the second version of MLPerf Inference. The tests expand beyond the original two for computer vision to include four covering the fastest-growing areas in AI: recommendation systems, natural language understanding, speech recognition and medical imaging.Organizations across a wide range of industries are already tapping into the NVIDIA® A100 Tensor Core GPU’s exceptional inference performance to take AI from their research groups into daily operations. Financial institutions are using conversational AI to answer customer questions faster; retailers are using AI to keep shelves stocked; and healthcare providers are using AI to analyze millions of medical images to more accurately identify disease and help save lives.“We’re at a tipping point as every industry seeks better ways to apply AI to offer new services and grow their business,” said Ian Buck, general manager and vice president of Accelerated Computing at NVIDIA. “The work we’ve done to achieve these results on MLPerf gives companies a new level of AI performance to improve our everyday lives.”The latest MLPerf results come as NVIDIA’s footprint for AI inference has grown dramatically. Five years ago, only a handful of leading high-tech companies used GPUs for inference. Now, with NVIDIA’s AI platform available through every major cloud and data center infrastructure provider, companies representing a wide array of industries are using its AI inference platform to improve their business operations and offer additional services.Additionally, for the first time, NVIDIA GPUs now offer more AI inference capacity in the public cloud than CPUs. Total cloud AI inference compute capacity on NVIDIA GPUs has been growing roughly 10x every two years.NVIDIA Takes AI Inference to New HeightsNVIDIA and its partners submitted their MLPerf 0.7 results using NVIDIA’s acceleration platform, which includes NVIDIA data center GPUs, edge AI accelerators and NVIDIA optimized software. NVIDIA A100, introduced earlier this year and featuring third-generation Tensor Cores and Multi-Instance GPU technology, increased its lead on the ResNet-50 test, beating CPUs by 30x versus 6x in the last round. Additionally, A100 outperformed the latest CPUs by up to 237x in the newly added recommender test for data center inference, according to the MLPerf Inference 0.7 benchmarks.This means a single NVIDIA DGX A100™ system can provide the same performance as about 1,000 dual-socket CPU servers, offering customers extreme cost efficiency when taking their AI recommender models from research to production.The benchmarks also show that NVIDIA T4 Tensor Core GPU continues to be a solid inference platform for mainstream enterprise, edge servers and cost-effective cloud instances. NVIDIA T4 GPUs beat CPUs by up to 28x in the same tests. In addition, the NVIDIA Jetson AGX Xavier™ is the performance leader among SoC-based edge devices.Achieving these results required a highly optimized software stack including NVIDIA TensorRT™ inference optimizer and NVIDIA Triton™ inference serving software, both available on NGC™, NVIDIA’s software catalog. In addition to NVIDIA’s own submissions, 11 NVIDIA partners submitted a total of 1,029 results using NVIDIA GPUs, representing over 85 percent of the total submissions in the data center and edge categories. About NVIDIA NVIDIA’s (NASDAQ: NVDA) invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots and self-driving cars that can perceive and understand the world. More information at https://nvidianews.nvidia.com/.For further information, contact: Kristin Uchiyama NVIDIA Corporation +1-408-313-0448 firstname.lastname@example.orgCertain statements in this press release including, but not limited to, statements as to: NVIDIA extending its lead on MLPerf benchmark and enabling businesses; NVIDIA breaking records; how organizations are using NVIDIA A100 Tensor Core GPUs; the benefits, performance and impact of NVIDIA GPUs, including NVIDIA A100, DGX A100, NVIDIA T4 Tensor Core GPU, NVIDIA Jetson AGX Xavier; industries seeking better ways to apply AI and grow their business; NVIDIA giving companies a new level of AI performance to improve our everyday lives; companies using NVIDIA’s AI inference platform to improve business operations and offer services; and NVIDIA taking AI inference to new heights are forward-looking statements that are subject to risks and uncertainties that could cause results to be materially different than expectations. Important factors that could cause actual results to differ materially include: global economic conditions; our reliance on third parties to manufacture, assemble, package and test our products; the impact of technological development and competition; development of new products and technologies or enhancements to our existing product and technologies; market acceptance of our products or our partners' products; design, manufacturing or software defects; changes in consumer preferences or demands; changes in industry standards and interfaces; unexpected loss of performance of our products or technologies when integrated into systems; as well as other factors detailed from time to time in the most recent reports NVIDIA files with the Securities and Exchange Commission, or SEC, including, but not limited to, its annual report on Form 10-K and quarterly reports on Form 10-Q. Copies of reports filed with the SEC are posted on the company's website and are available from NVIDIA without charge. These forward-looking statements are not guarantees of future performance and speak only as of the date hereof, and, except as required by law, NVIDIA disclaims any obligation to update these forward-looking statements to reflect future events or circumstances.© 2020 NVIDIA Corporation. All rights reserved. NVIDIA, the NVIDIA logo, DGX A100, Jetson AGX Xavier, NGC, NVIDIA Triton and TensorRT are trademarks and/or registered trademarks of NVIDIA Corporation in the U.S. and other countries. All other trademarks and copyrights are the property of their respective owners.
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(Bloomberg) -- Chinese technology companies including Huawei Technologies Co. have expressed strong concerns to local regulators about Nvidia Corp.’s proposed acquisition of Arm Ltd., people familiar with the matter said, potentially jeopardizing the $40 billion semiconductor deal.Several of the country’s most influential tech firms have been lobbying the State Administration for Market Regulation to either reject the transaction or impose conditions to ensure their access to Arm technology, the people said. Chief among their concerns is that Nvidia may force the British firm to cut off Chinese clients, they said, asking not to be identified discussing private deliberations.China’s fear is that Arm -- whose semiconductor designs and architecture are central to most of the world’s electronics from smartphones to supercomputers -- will become yet another pawn in a U.S.-Chinese struggle for tech supremacy. Nvidia is buying the British firm from Japan’s SoftBank Group Corp., bringing it under American jurisdiction and theoretically threatening its cherished status as a neutral party in the chip industry. SoftBank’s shares erased gains Wednesday to close slightly lower in Tokyo.Any review of the deal in Beijing is likely to be colored by what it perceives as growing U.S. attempts to contain its largest technology companies. It has the power to approve the deal because China is the world’s largest market for semiconductors, importing about $300 billion worth of chips annually. That dependence on foreign silicon may convince regulators there to try and wring major concessions from Nvidia to preserve the Arm relationship, for instance by keeping the business independent and separate.“I doubt why China would make it easy, since allowing Nvidia to take over Arm could worsen Huawei’s access to the U.K. company’s chip design,” Bloomberg Intelligence analyst Anthea Lai said. Arm designs are fundamental to a plethora of the company’s products, including its Kirin smartphone processors, Kunpeng server chips and Ascend for AI applications.Read more: Nvidia Deal Threatens Arm’s Role as the Switzerland of ChipsA Huawei representative declined to comment. The Chinese regulatory agency didn’t respond to calls and a faxed request for comment. Nvidia representatives pointed to remarks this month from Chief Executive Officer Jensen Huang, who expressed confidence the deal will pass muster.“As soon as we explain the rationale of the transaction and our plans, the regulators around the world will realize that these are two complementary companies,” Huang said at Arm’s developer conference. “The two companies being complementary when combined will create new innovations, which is good for the market.”Nvidia’s record deal to buy Arm was always expected to encounter major hurdles from regulators in countries sparring over trade, as well as customers concerned the transaction will limit competition and unfairly favor Arm’s future owner. The Chinese watchdog has yet to view a formal application for approval, but the opposition there is likely to be fiercest given its reliance on American technology at a time of mounting U.S. hostility. Beijing’s authority has proven fatal for at least one previous chip deal: Qualcomm Inc. gave up its pursuit of NXP Semiconductors NV in 2018 after failing to win approval from China over more than 21 months.What Bloomberg Intelligence SaysClearance in China will likely be the biggest challenge and take the most time. Because China’s government could use Nvidia’s deal approval as a pawn in its trade conflicts with the U.S., as some believe it did with Qualcomm-NXP, it’s difficult to predict yet whether the purchase will clear there. Still, the ability to impose conditions allows China to extract advantageous licensing terms for Chinese companies, which may be viewed as the better route.\- Jennifer Rie and Aitor Ortiz, analystsClick here for the research.China has determined it must build its own world-class chip industry, given rising tensions with the U.S. administration of Donald Trump. That goal is unlikely to be affected by the American elections in November, although the outcome may change the dynamics between the two countries and by extension the Arm review.Read more: China Said to Plan Broad Chip Sector Support to Fight TrumpNvidia is a major provider of processors for computers and high-end computing, pitting it against players from Intel Corp. to Qualcomm and Huawei. And Arm’s designs and instruction set -- the code used by chips to communicate with software -- are an integral element of phones, self-driving cars and billions of sensors. They’re also growing more essential for servers and laptops.The Cambridge, U.K.-based company has thrived on its neutrality as the Switzerland of the industry: it licenses technology to hundreds of companies, competing with none of them. While the Nvidia acquisition threatens this, executives have argued it’s in their best interest to maintain Arm’s neutrality to avoid alienating potential customers.The deal still needs sign-offs from China, the U.K., the European Union and the U.S., a process that often requires government agencies to solicit or be open to comment from customers and competitors. Nvidia and Arm have said they’re confident they’ll get through it but it may take as long as 18 months to secure the necessary approvals.Read more: Nvidia Buys SoftBank’s Arm in Record $40 Billion Chip Deal(Updates with SoftBank’s shares and analyst’s comment from the third paragraph)For more articles like this, please visit us at bloomberg.comSubscribe now to stay ahead with the most trusted business news source.©2020 Bloomberg L.P.