Intel Nervana Neural Network Processors (NNP), premiers ASICs conçus pour l’IA et le Deep Learning

Intel accélère le développement, le déploiement et les performances de l’intelligence artificielle avec une nouvelle classe de matériel d’intelligence artificielle, du cloud à l’edge

Intel vient de dévoiler le futur de d’intelligence artificielle (IA) en présentant les nouveaux produits conçus pour accélérer le développement et le déploiement de systèmes d’IA cloud-to-edge.

Intel a présenté ses processeurs Intel Nervana Neural Network Processors (NNP) pour la formation (NNP-T1000) et l’inférence (NNP-I1000) – les premiers ASICs d’Intel spécialement conçus pour le Deep Learning complexe, avec une échelle et une efficacité sans commune mesure pour les utilisateurs de cloud et de datacenter.

A photo shows the Intel Nervana NNP-T for training, Mezzanine card. Intel Nervana Neural Network Processors are Intel’s first purpose-built ASICs for complex deep learning with scale and efficiency for cloud and data center customers. Intel demonstrated the Intel NNPs at the company’s AI Summit on Nov. 12, 2019, in San Francisco. (Credit: Intel Corporation)

Intel a également dévoilé sa nouvelle génération de processeurs Intel Movidius Myriad Vision Processing Unit (VPU) pour le Edge Media, la vision par ordinateur et les applications d’inférence.

Ces produits renforcent le portefeuille de solutions d’intelligence artificielle d’Intel, qui devrait générer plus de 3,5 milliards de dollars de revenus en 2019. La portfolio de solutions IA d’Intel, le plus large et le plus complet du secteur, aide les clients à développer et déployer des modèles d’intelligence artificielle à n’importe quelle échelle, des cloud massifs aux plus petits périphériques de pointe.

A photo shows the Intel Nervana NNP-T for training, Mezzanine card. Intel Nervana Neural Network Processors are Intel’s first purpose-built ASICs for complex deep learning with scale and efficiency for cloud and data center customers. Intel demonstrated the Intel NNPs at the company’s AI Summit on Nov. 12, 2019, in San Francisco. (Credit: Intel Corporation)

L’annonce originale (anglais)

Intel Speeds AI Development, Deployment and Performance with New Class of AI Hardware from Cloud to Edge

What’s New: Today at a gathering of industry influencers, Intel welcomed the next wave of artificial intelligence (AI) with updates on new products designed to accelerate AI system development and deployment from cloud to edge. Intel demonstrated its Intel® Nervana™ Neural Network Processors (NNP) for training (NNP-T1000) and inference (NNP-I1000) — Intel’s first purpose-built ASICs for complex deep learning with incredible scale and efficiency for cloud and data center customers. Intel also revealed its next-generation Intel® Movidius™ Myriad™ Vision Processing Unit (VPU) for edge media, computer vision and inference applications.

“With this next phase of AI, we’re reaching a breaking point in terms of computational hardware and memory. Purpose-built hardware like Intel Nervana NNPs and Movidius Myriad VPUs are necessary to continue the incredible progress in AI. Using more advanced forms of system-level AI will help us move from the conversion of data into information toward the transformation of information into knowledge.” – Naveen Rao, Intel corporate vice president and general manager of the Intel Artificial Intelligence Products Group

Why They Are Important: These products further strengthen Intel’s portfolio of AI solutions, which is expected to generate more than $3.5 billion in revenue in 2019. The broadest in breadth and depth in the industry, Intel’s AI portfolio helps customers enable AI model development and deployment at any scale from massive clouds to tiny edge devices, and everything in between.

What Intel Announced: Now in production and being delivered to customers, the new Intel Nervana NNPs are part of a systems-level AI approach offering a full software stack developed with open components and deep learning framework integration for maximum use.

The Intel Nervana NNP-T strikes the right balance between compute, communication and memory, allowing near-linear, energy-efficient scaling from small clusters up to the largest pod supercomputers. The Intel Nervana NNP-I is power- and budget-efficient and ideal for running intense, multi-modal inference at real-world scale using flexible form factors. Both products were developed for the AI processing needs of leading-edge AI customers like Baidu and Facebook.

“We are excited to be working with Intel to deploy faster and more efficient inference compute with the Intel Nervana Neural Network Processor for inference (NNP-I) and to extend support for our state-of-the-art deep learning compiler, Glow, to the NNP-I,” – Misha Smelyanskiy, Facebook director of AI System Co-Design

Additionally, Intel’s next-generation Intel Movidius VPU, scheduled to be available in the first half of 2020, incorporates unique, highly efficient architectural advances that are expected to deliver leading performance—more than 10 times the inference performance as the previous generation—with up to six times the power efficiency of competitor processors. Intel also announced its new Intel® DevCloud for the Edge, which along with the Intel® Distribution of OpenVINO™ toolkit, addresses a key pain point for developers—allowing them to try, prototype and test AI solutions on a broad range of Intel processors before they buy hardware.

Why It Matters: Incredibly complex data, models and techniques are required to advance deep learning reasoning and context, bringing about a need to think differently about architectures.

With most of the world running some part of its AI on Intel® Xeon® Scalable processors, Intel continues to improve this platform with features like Intel® Deep Learning Boost with Vector Neural Network Instruction (VNNI) that bring enhanced AI inference performance across the data center and edge deployments. While that will continue to serve as a strong AI foundation for years, the most advanced deep learning training needs for Intel customers call for performance to double every 3.5 months, and those types of breakthroughs will only happen with a portfolio of AI solutions like Intel’s. Intel is equipped to look at the full picture of computing, memory, storage, interconnect, packaging and software to maximize efficiency, programmability and ensure the critical ability to scale up distributing deep learning across thousands of nodes to, in turn, scale the knowledge revolution.

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