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1000x Faster Deep-Learning at Petascale Using Intel Xeon Phi Processors

A cumulative effort over several years to scale the training of deep-learning neural networks has resulted in the first demonstration of petascale deep-learning training performance, and further to deliver this performance when solving real science problems. The result reflects the combined efforts of NERSC (National Energy Research Scientific Computing Center), Stanford and Intel to solve real world use cases rather than simply report on performance benchmarks.

FPGAs Power New Intel Programmable Acceleration Cards

Today, Intel announced a comprehensive hardware and software platform solution to enable faster deployment of customized field programmable gate array (FPGA)-based acceleration of networking, storage and computing workloads. “Intel is making it easier for server equipment makers such as Dell EMC to exploit FPGA technology for data acceleration as a ready-to-use platform,” said Dan McNamara, corporate vice president and general manager of Intel’s Programmable Solutions Group. “With our ecosystem partners, we are enabling the industry with point solutions with a substantial boost in performance while preserving power and cost budgets.”

Radio Free HPC Looks at China’s 95 Petaflop Tianhe-2A Supercomputer

In this podcast, the Radio Free HPC team looks at China’s massive upgrade of the Tianhe-2A supercomputer to 95 Petaflops peak performance. “As detailed in a new 21-page report by Jack Dongarra from the University of Tennessee, the upgrade should nearly double the performance of the system, which is currently ranked at #2 on TOP500.”

Freshly Funded Optalysys Optical Processing to Speed Genomics

Optalysys, a start-up pioneering the development of light-speed optical coprocessors, today announced the company raised 3.95 million U.S. dollars from angel investors. Optalysys will use the funds to manufacture the first commercially available high-performance computing processor based on its patented optical processing technology.

Intel Discontinues Xeon Phi 7200-Series Knights Landing Coprocessors

AnandTech reports that Intel is discontinuing it’s line of Knights Landing PCIe based Co-processors. The move is not a surprise given that the company has been producing bootable Xeon Phi processors since early in 2016. “At least for now, Intel does not want to compete against add-on PCIe compute accelerators with its Xeon Phi products. A big question is whether it actually needs to, given the stand-alone capabilities of Xeon Phi and its performance characteristics.”

Intel Processors for Machine Learning

Machine Learning is a hot topic for many industries and is showing tremendous promise to change how we use systems. From design and manufacturing to searching for cures for diseases, machine learning can be a great disrupter, when implemented to take advantage of the latest processors.

New ARM Architecture Targets AI

ARM has taken a step into the artificial intelligence market with the announcement of a new micro-architecture – DynamIQ – specifically designed for artificial intelligence (AI). “DynamIQ technology is a monumental shift in multi-core microarchitecture for the industry and the foundation for future ARM Cortex-A processors. The flexibility and versatility of DynamIQ will redefine the multi-core experience across a greater range of devices from edge to cloud across a secure, common platform.”

Intel MPI Library 2017 Focuses on Intel Multi-core/Many-Core Clusters

With the release of Intel Parallel Studio XE 2017, the focus is on making applications perform better on Intel architecture-based clusters. Intel MPI Library 2017, a fully integrated component of Intel Parallel Studio XE 2017, implements the high-performance MPI-3.1 specification on multiple fabrics. It enables programmers to quickly deliver the best parallel performance, even if you change or upgrade to new interconnects, without requiring changes to the software or operating environment.

AWS Adds FPGAs to its Public Cloud

Amazon Web Services chief evangelist Jeff Barr announced in a recent blog post that the company was adding Xilinx FPGAs to its Amazon Elastic Compute Cloud (Amazon EC2). The addition of this new hardware will allow users to create accelerated FPGA applications, but AWS will also let users sell these applications on the AWS Marketplace. “We are giving you the ability to design your own logic, simulate and verify it using cloud-based tools, and then get it to market in a matter of days,” said Barr.

Optimizing Your Code for Big Data

Libraries that are tuned to the underlying hardware architecture can increase performance tremendously. Higher level libraries such at the Intel Data Analytics Acceleration Library (Intel DAAL) can assist the developer with highly tuned algorithms for data analysis as well as machine learning. Intel DAAL functions can be called within other, more comprehensive frameworks that deal with the various types of data and storage, increasing the performance and lowering the development time of a wide range of applications.