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AWS Leverages Habana Gaudi AI Processors

Today at AWS re:Invent 2020, AWS CEO Andy Jassy announced EC2 instances that will leverage up to eight Habana Gaudi accelerators and deliver up to 40% better price performance than current graphics processing unit-based EC2 instances for machine learning workloads. Gaudi accelerators are specifically designed for training deep learning models for workloads that include natural language processing, object detection and machine learning training, classification, recommendation and personalization.

"We are proud that AWS has chosen Habana Gaudi processors for its forthcoming EC2 training instances. The Habana team looks forward to our continued collaboration with AWS to deliver on a roadmap that will provide customers with continuity and advances over time." -David Dahan, chief executive officer at Habana Labs, an Intel Company.

Apple Announces New Line of MacBooks and Mac Minis Powered by M1

On a momentous day for the Mac, Apple today introduced a new MacBook Air, 13-inch MacBook Pro, and Mac mini powered by the revolutionary M1, the first in a family of chips designed by Apple specifically for the Mac. By far the most powerful chip Apple has ever made, M1 transforms the Mac experience. With its industry-leading performance per watt, together with macOS Big Sur, M1 delivers up to 3.5x faster CPU, up to 6x faster GPU, up to 15x faster machine learning (ML) capabilities, and battery life up to 2x longer than before. And with M1 and Big Sur, users get access to the biggest collection of apps ever for Mac. With amazing performance and remarkable new features, the new lineup of M1-powered Macs are an incredible value, and all are available to order today.

"The introduction of three new Macs featuring Apple's breakthrough M1 chip represents a bold change that was years in the making, and marks a truly historic day for the Mac and for Apple," said Tim Cook, Apple's CEO. "M1 is by far the most powerful chip we've ever created, and combined with Big Sur, delivers mind-blowing performance, extraordinary battery life, and access to more software and apps than ever before. We can't wait for our customers to experience this new generation of Mac, and we have no doubt it will help them continue to change the world."

Tachyum Prodigy Native AI Supports TensorFlow and PyTorch

Tachyum Inc. today announced that it has further expanded the capabilities of its Prodigy Universal Processor through support for TensorFlow and PyTorch environments, enabling a faster, less expensive and more dynamic solution for the most challenging artificial intelligence/machine learning workloads.

Analysts predict that AI revenue will surpass $300 billion by 2024 with a compound annual growth rate (CAGR) of up to 42 percent through 2027. AI is being heavily invested in by technology giants looking to make the technology more accessible for enterprise use-cases. They include self-driving vehicles to more sophisticated and control-intensive disciplines like Spiking Neural Nets, Explainable AI, Symbolic AI and Bio AI. When deployed into AI environments, Prodigy is able to simplify software processes, accelerate performance, save energy and better incorporate rich data sets to allow for faster innovation.

Lightmatter Introduces Optical Processor to Speed Compute for Next-Gen AI

Lightmatter, a leader in silicon photonics processors, today announces its artificial intelligence (AI) photonic processor, a general-purpose AI inference accelerator that uses light to compute and transport data. Using light to calculate and communicate within the chip reduces heat—leading to orders of magnitude reduction in energy consumption per chip and dramatic improvements in processor speed. Since 2010, the amount of compute power needed to train a state-of-the-art AI algorithm has grown at five times the rate of Moore's Law scaling—doubling approximately every three and a half months. Lightmatter's processor solves the growing need for computation to support next-generation AI algorithms.

"The Department of Energy estimates that by 2030, computing and communications technology will consume more than 8 percent of the world's power. Transistors, the workhorse of traditional processors, aren't improving; they're simply too hot. Building larger and larger datacenters is a dead end path along the road of computational progress," said Nicholas Harris, PhD, founder and CEO at Lightmatter. "We need a new computing paradigm. Lightmatter's optical processors are dramatically faster and more energy efficient than traditional processors. We're simultaneously enabling the growth of computing and reducing its impact on our planet."

GIGABYTE Introduces a Broad Portfolio of G-series Servers Powered by NVIDIA A100 PCIe

GIGABYTE, an industry leader in high-performance servers and workstations, announced its G-series servers' validation plan. Following the NVIDIA A100 PCIe GPU announcement today, GIGABYTE has completed the compatibility validation of the G481-HA0 / G292-Z40 and added the NVIDIA A100 to the support list for these two servers. The remaining G-series servers will be divided into two waves to complete their respective compatibility tests soon. At the same time, GIGABYTE also launched a new G492 series server based on the AMD EPYC 7002 processor family, which provides PCIe Gen4 support for up to 10 NVIDIA A100 PCIe GPUs. The G492 is a server with the highest computing power for AI models training on the market today. GIGABYTE will offer two SKUs for the G492. The G492-Z50 will be at a more approachable price point, whereas the G492-Z51 will be geared towards higher performance.

The G492 is GIGABYTE's second-generation 4U G-series server. Based on the first generation G481 (Intel architecture) / G482 (AMD architecture) servers, the user-friendly design and scalability have been further optimized. In addition to supporting two 280 W 2nd Gen AMD EPYC 7002 processors, the 32 DDR4 memory slots support up to 8 TB of memory and maintain data transmission at 3200 MHz. The G492 has built-in PCIe Gen4 switches, which can provide more PCIe Gen4 lanes. PCIe Gen4 has twice the I/O performance of PCIe Gen3 and fully enables the computing power of the NVIDIA A100 Tensor Core GPU, or it can be applied to PCIe storage to help provide a storage upgrade path that is native to the G492.

Intel Announces "Cooper Lake" 4P-8P Xeons, New Optane Memory, PCIe 4.0 SSDs, and FPGAs for AI

Intel today introduced its 3rd Gen Intel Xeon Scalable processors and additions to its hardware and software AI portfolio, enabling customers to accelerate the development and use of AI and analytics workloads running in data center, network and intelligent-edge environments. As the industry's first mainstream server processor with built-in bfloat16 support, Intel's new 3rd Gen Xeon Scalable processors makes artificial intelligence (AI) inference and training more widely deployable on general-purpose CPUs for applications that include image classification, recommendation engines, speech recognition and language modeling.

"The ability to rapidly deploy AI and data analytics is essential for today's businesses. We remain committed to enhancing built-in AI acceleration and software optimizations within the processor that powers the world's data center and edge solutions, as well as delivering an unmatched silicon foundation to unleash insight from data," said Lisa Spelman, Intel corporate vice president and general manager, Xeon and Memory Group.

AMD Announces Radeon Pro VII Graphics Card, Brings Back Multi-GPU Bridge

AMD today announced its Radeon Pro VII professional graphics card targeting 3D artists, engineering professionals, broadcast media professionals, and HPC researchers. The card is based on AMD's "Vega 20" multi-chip module that incorporates a 7 nm (TSMC N7) GPU die, along with a 4096-bit wide HBM2 memory interface, and four memory stacks adding up to 16 GB of video memory. The GPU die is configured with 3,840 stream processors across 60 compute units, 240 TMUs, and 64 ROPs. The card is built in a workstation-optimized add-on card form-factor (rear-facing power connectors and lateral-blower cooling solution).

What separates the Radeon Pro VII from last year's Radeon VII is full double precision floating point support, which is 1:2 FP32 throughput compared to the Radeon VII, which is locked to 1:4 FP32. Specifically, the Radeon Pro VII offers 6.55 TFLOPs double-precision floating point performance (vs. 3.36 TFLOPs on the Radeon VII). Another major difference is the physical Infinity Fabric bridge interface, which lets you pair up to two of these cards in a multi-GPU setup to double the memory capacity, to 32 GB. Each GPU has two Infinity Fabric links, running at 1333 MHz, with a per-direction bandwidth of 42 GB/s. This brings the total bidirectional bandwidth to a whopping 168 GB/s—more than twice the PCIe 4.0 x16 limit of 64 GB/s.

ASUS Announces Tinker Edge R with AI Machine-Learning Capabilities

ASUS today announced Tinker Edge R, a single-board computer (SBC) specially designed for AI applications. It uses a Rockchip RK3399Pro NPU, a machine-learning (ML) accelerator that speeds up processing efficiency, lowers power demands and makes it easier to build connected devices and intelligent applications.

With this integrated ML accelerator, Tinker Edge R can perform three tera-operations per second (3 TOPS), using low power consumption. It also features an optimized neural-network (NN) architecture, which means Tinker Edge R can support multiple ML frameworks and allow lots of common ML models to be compiled and run easily.
ASUS Tinker Edge R

Arm Delivers New Edge Processor IPs for IoT

Today, Arm announced significant additions to its artificial intelligence (AI) platform, including new machine learning (ML) IP, the Arm Cortex -M55 processor and Arm Ethos -U55 NPU, the industry's first microNPU (Neural Processing Unit) for Cortex-M, designed to deliver a combined 480x leap in ML performance to microcontrollers. The new IP and supporting unified toolchain enable AI hardware and software developers with more ways to innovate as a result of unprecedented levels of on-device ML processing for billions of small, power-constrained IoT and embedded devices.

Intel Announces Broadest Product Portfolio for Moving, Storing, and Processing Data

Intel Tuesday unveiled a new portfolio of data-centric solutions consisting of 2nd-Generation Intel Xeon Scalable processors, Intel Optane DC memory and storage solutions, and software and platform technologies optimized to help its customers extract more value from their data. Intel's latest data center solutions target a wide range of use cases within cloud computing, network infrastructure and intelligent edge applications, and support high-growth workloads, including AI and 5G.

Building on more than 20 years of world-class data center platforms and deep customer collaboration, Intel's data center solutions target server, network, storage, internet of things (IoT) applications and workstations. The portfolio of products advances Intel's data-centric strategy to pursue a massive $300 billion data-driven market opportunity.

Micron 5210 ION SSD Now Generally Available

Micron Technology, Inc., today announced the next step towards market leadership for its quad-level cell (QLC) NAND technology with immediate broad market availability of the popular Micron 5210 ION enterprise SATA SSD, the world's first QLC SSD, which began shipping to select customers and partners in May of this year. Available through global distributors, the Micron 5210 ION enterprise SATA SSD further accelerates Micron's lead in the QLC market, enabling replacement of hard disk drives (HDDs) with SSDs and building on Micron's recent launch of the Crucial P1 NVMe QLC SSD for consumer markets.

Enterprise storage needs are increasing as data center applications deliver real-time user insights and intelligent and enhanced user experiences, leveraging artificial intelligence (AI), machine learning, big data and real-time analytics. At the same time, there is a growing consumer need for higher storage capacity to support digital experiences. QLC SSDs are uniquely designed to address these requirements.

QNAP Introduces the TS-2888X AI-ready NAS

QNAP Systems, Inc. introduces the brand-new TS-2888X AI-Ready NAS, an all-in-one AI solution combining robust storage and a ready-to-use software environment that simplifies AI workflows with high cost-efficiency. Built using next-gen Intel Xeon W processors with up to 18 cores and employing a hybrid storage architecture with eight hard drives and twenty high-performance SSDs (including 4 U.2 SSDs), the TS-2888X also supports installing up to 4 high-end graphics cards and runs QNAP's AI developer package "QuAI". The TS-2888X packs everything required for machine learning AI to help organizations quickly and easily implement AI applications.

"Compared with typical AI workstations, the TS-2888X combines high-performance computing with huge-capacity storage to greatly reduce latency, accelerate data transfer, and to eliminate performance bottlenecks caused by network connectivity," said David Tsao, Product Manager of QNAP, adding "integrating AI-focused hardware and software reduces the time and complexity for implementing and managing AI tasks, making the TS-2888X the ideal AI solution for most organizations."

AMD and Xilinx Announce a New World Record for AI Inference

At today's Xilinx Developer Forum in San Jose, Calif., our CEO, Victor Peng was joined by the AMD CTO Mark Papermaster for a Guinness. But not the kind that comes in a pint - the kind that comes in a record book. The companies revealed the AMD and Xilinx have been jointly working to connect AMD EPYC CPUs and the new Xilinx Alveo line of acceleration cards for high-performance, real-time AI inference processing. To back it up, they revealed a world-record 30,000 images per-second inference throughput!

The impressive system, which will be featured in the Alveo ecosystem zone at XDF today, leverages two AMD EPYC 7551 server CPUs with its industry-leading PCIe connectivity, along with eight of the freshly-announced Xilinx Alveo U250 acceleration cards. The inference performance is powered by Xilinx ML Suite, which allows developers to optimize and deploy accelerated inference and supports numerous machine learning frameworks such as TensorFlow. The benchmark was performed on GoogLeNet, a widely used convolutional neural network.

VIA Launches ALTA DS 3 Edge AI System Powered by Qualcomm Snapdragon 820E

VIA Technologies, Inc., today announced the launch of the VIA ALTA DS 3 Edge AI system. Powered by the Qualcomm Snapdragon 820E Embedded Platform, the system enables the rapid development and deployment of intelligent signage, kiosk, and access control devices that require real-time image and video capture, processing, and display capabilities.

The VIA ALTA DS 3 harnesses the cutting-edge compute, graphics, and AI processing capabilities of the Qualcomm Snapdragon 820E Embedded Platform to facilitate the creation of vibrant new user experiences by allowing customers to combine their own AI applications with immersive multimedia signage display content in a compact, low-power system.

The Laceli AI Compute Stick is Here to Compete Against Intel's Movidius

Gyrfalcon Technology Inc, an emerging AI chip maker in Silicon Valley, CA, launches its Laceli AI Compute Stick after Intel Movidius announced its deep learning Neural Compute Stick in July of last year. With the company's first ultra-low power, high performance AI processor Lightspeeur 2801S, the Laceli AI Compute Stick runs a 2.8 TOPS performance within 0.3 Watt of power, which is 90 times more efficient than the Movidius USB Stick (0.1 TOPS within 1 Watt of power.)

Lightspeeur is based on Gyrfalcon Technology Inc's APiM architecture, which uses memory as the AI processing unit. This eliminates the huge data movement that results in high power consumption. The architecture features true, on-chip parallelism, in situ computing, and eliminates memory bottlenecks. It has roughly 28,000 parallel computing cores and does not require external memory for AI inference.
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