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OpenHPC Moves Forward with New Software Release

In this video from ISC 2016, Karl Schultz from the OpenHPC Community provides and update on software releases and other milestones. “OpenHPC is a Linux Foundation Collaborative Project whose mission is to provide an integrated collection of HPC-centric components that can be used to provide full-featured reference HPC software stacks. Provided components should range across the entire HPC software ecosystem including provisioning and system administration tools, resource management, I/O services, development tools, numerical libraries, and performance analysis tools.”

Dell & OpenHPC at ISC 2016

In this video from ISC 2016, Onur Celebioglu from Dell describes how the company is working with the OpenHPC Community to ease the deployment of high performance computing solutions. “Community investment in open source frameworks and open standards is the right way to ensure the right capabilities are available to a growing HPC community. The new OpenHPC effort will greatly accelerate HPC adoption, productive usage and innovation. As a long-time leader in democratizing HPC, Dell is proud to be a founding member of this effort.”

SUSE Powers OpenHPC at ISC 2016

With the OpenHPC stack, you can leap forward with a validated, tested and secure infrastructure software stack and get to product in a fraction of the time. This new approach will drive rapid advances in the state of the art and accelerate our progress towards true exascale computing. “SUSE, as a founder and board member of OpenHPC, contributes not just to the Linux OS elements of the project but also to the underlying HPC system building componentry and system tools that can bridge today’s infrastructure development gaps and help move vendors and researchers rapidly towards powerful HPC solution stacks.”

Video: Bob Wisniewski on OpenHPC at ISC 2016

In this video from ISC 2016, Bob Wisniewski from Intel provides an update on OpenHPC community activities. “OpenHPC is a collaborative, community effort that initiated from a desire to aggregate a number of common ingredients required to deploy and manage High Performance Computing (HPC) Linux clusters including provisioning tools, resource management, I/O clients, development tools, and a variety of scientific libraries. Packages provided by OpenHPC have been pre-built with HPC integration in mind with a goal to provide re-usable building blocks for the HPC community. Over time, the community also plans to identify and develop abstraction interfaces between key components to further enhance modularity and interchangeability.”

Intel Furthers Machine Learning Capabilities

“Intel provided a wealth of machine learning announcements following the Intel Xeon Phi processor (formerly known as Knights Landing) announcement at ISC’16. Building upon the various technologies in Intel Scalable System Framework, the machine learning community can expect up to 38% better scaling over GPU-accelerated machine learning and an up to 50x speedup when using 128 Intel Xeon Phi nodes compared to a single Intel Xeon Phi node. The company also announced an up to 30x improvement in inference performance (also known as scoring or prediction) on the Intel Xeon E5 product family due to an optimized Intel Caffe plus Intel Math Kernel Library (Intel® MKL) package.”

Intel Xeon Phi Developer Access Platform at ISC 2016

In this video from ISC 2016, Kirti Devi from Intel describes the new Intel Developer Platform for the Intel Xeon Phi processor. “With this program, Intel and its partner Colfax are widening early levels of access, support and training for the widely anticipated next-generation Intel Xeon Phi processor release. The Developer Access Program gives developers the opportunity to begin leveraging key new capabilities in the processor before they are generally available. That means developers will have time to work to parallelize and vectorize their code and look for opportunities to exploit the massive performance capabilities that KNL offers so workloads are ready for prime time when customers deploy their next-generation systems.”

Intel to Distribute SUSE High Performance Computing Stack

“The SUSE and Intel collaboration on Intel HPC Orchestrator and OpenHPC puts this power within reach of a whole new range of industries and enterprises that need data-driven insights to compete and advance. This is an industry-changing approach that will rapidly accelerate HPC innovation and advance the state of the art in a way that creates real-world benefits for our customers and partners.”

Video: Announcing Intel HPC Orchestrator

In this video from ISC 2016, Figen Ulgen from Intel describes the new Intel HPC Orchestrator. “Intel HPC Orchestrator simplifies the installation, management and ongoing maintenance of a high-performance computing system by reducing the amount of integration and validation effort required for the HPC system software stack. Intel HPC Orchestrator can help accelerate your time to results and value in your HPC initiatives. With Intel HPC Orchestrator, based on the OpenHPC system software stack, you can take advantage of the innovation driven by the open source community – while also getting peace of mind from Intel support across the stack.”

Allinea DDT Debugger to be Used for 25 Petaflop Supercomputer at JCAHP in Japan

Today Allinea Software announced that the Joint Center for Advanced High Performance Computing (JCAHPC) in Japan will use the Allinea DDT debugger for its new supercomputer. Coming online in December 2016, the new supercomputer, known as Oakforest-PACS, will be the fastest supercomputer system in Japan with 25 PFLOPS on Intel’s Xeon Phi (Knights Landing) manycore processors and the Omni-Path architecture.

Helping the Compiler Speed Intel Xeon Phi

The vector parallel capabilities of the Intel Xeon Phi coprocessor are similar in many ways with vectorizing code for the main CPU. The performance improvement when coding smartly and using the tools available can be tremendous. Since the Intel Xeon Phi coprocessor can show very large gains in performance due to its extra wide processing units. “Although it is time consuming to look at each and every loop in a large application, by doing so, and both telling the compiler what to do, and letting the compiler do its work, performance increases can be quite large, leading to shorter run times and/or more complete results.”