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Reliability, Scalability and Performance – the Impact of Intel HPC Orchestrator

When it comes to getting the performance out of your HPC system, it’s the small things that count. David Lombard, Sr. Principal Engineer at Intel Corporation, explains. ” Intel HPC Orchestrator encapsulates the important tradeoffs, and pays attention to the small details that can greatly impact how well the underlying features of the hardware are leveraged to deliver better performance and scalability.”

Rock Stars of HPC: Karan Batta

From software developer at a small start-up in New Zealand, to Senior Program Manager at one of the largest multinational technology companies in the US, Karan Batta has led a career touched by HPC – even if he didn’t always realize it at the time. As the driving force behind the GPU Infrastructure vision, roadmap and deployment in Microsoft Azure, Karan Batta is a Rock Star of HPC.

Rock Stars of HPC: James Phillips

Recipient of a Gordon Bell Award in 2002, James Phillips has been a full-time research programmer for almost 20 years. Since 1998, he has been the lead developer of NAMD, a parallel molecular dynamics code designed for high-performance simulation of large biomolecular systems that scales beyond 200,000 cores, and is undoubtedly a Rock Star of HPC.

Intel Advisor Roofline Analysis Finds New Opportunities for Optimizing Application Performance

Intel Advisor, an integral part of Intel Parallel Studio XE 2017, can help identify portions of code that could be good candidates for parallelization (both vectorization and threading). It can also help determine when it might not be appropriate to parallelize a section of code, depending on the platform, processor, and configuration it’s running on. Intel Advisor Roofline Analysis reveals the gap between an application’s performance and its expected performance.

Intel® HPC Orchestrator – Simplifying HPC

“Like OpenHPC on which it is based, Intel HPC Orchestrator is a middleware stack for HPC environments that sits on top of the base operating system and provides everything needed to run a variety of HPC applications from independent software vendors together on the same HPC system. The product includes tools for administration, provisioning, resource and workload management, HPC runtimes, I/O services, scientific libraries, MPI libraries, compilers and other development tools.”

HPC Moves to the Cloud – What You Need to Know

While some domains that rely on computing systems are satisfied with the performance gains that are continuously delivered from processor manufacturers, others require performance that can only be attained through massive parallelism. High-performance computing is for those that need the highest performance in order to solve many of today’s most difficult scientific challenges.

Intel® VTune™ Amplifier Turns Raw Profiling Data Into Performance Insights

Discovering where the performance bottlenecks are and knowing what to do about it can be a mysterious and complex art, needing some very sophisticated performance analysis tools for success. That’s where Intel® VTune™ Amplifier XE 2017, part of Intel Parallel Studio XE, comes in.

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.

Intel Releases Optimized Python for HPC

“By implementing popular Python packages such as NumPy, SciPy, scikit-learn, to call the Intel Math Kernel Library (Intel MKL) and the Intel Data Analytics Acceleration Library (Intel DAAL), Python applications are automatically optimized to take advantage of the latest architectures. These libraries have also been optimized for multithreading through calls to the Intel Threading Building Blocks (Intel TBB) library. This means that existing Python applications will perform significantly better merely by switching to the Intel distribution.”

Deep Learning in HPC – Using Data to Go Far Beyond Automation in Pathology

Dr. Amit Seti from IIT-Gauwhati presented this talk at GTCx in India. “This talk will cover how medical imaging data can be used to train computer vision systems that automate diagnostic analysis in current clinical practice. Not only that, with more creative use of data, we can go even beyond that to predict outcome of specific treatment for individual patients. We will cover results from prostate and breast cancers to show that a future is not too far where algorithms will become a necessary set of tools in a pathologist’s toolbox.”