In the podcast, Mike Bernhardt from ECP catches up with Sameer Shende to learn how the Performance Research Lab at the University of Oregon is helping to pave the way to Exascale. “Developers of parallel computing applications can well appreciate the Tuning and Analysis Utilities (TAU) performance evaluation tool—it helps them optimize their efforts. Sameer has worked with the TAU software for nearly two and a half decades and has released more than 200 versions of it. Whatever your application looks like, there’s a good chance that TAU can support it and help you improve your performance.”
Latest Intel Tools Make Code Modernization Possible
December 21, 2018 by Leave a Comment
Code modernization means ensuring that an application makes full use of the performance potential of the underlying processors. And that means implementing vectorization, threading, memory caching, and fast algorithms wherever possible. But where do you begin? How do you take your complex, industrial-strength application code to the next performance level?
Development Tools are More Important Now Than Ever
November 30, 2018 by Leave a Comment
In this video, Sanjiv Shah, Vice President of the Core Visual Computing Group, and General Manager of Technical, Enterprise, and Cloud Computing Software Tools at Intel offers his perspective on the evolving nature of the developer’s role, and the latest resources to address persistent issues in application coding.
Artificial Intelligence and Cloud-to-edge Acceleration
November 27, 2018 by Leave a Comment
In this video, Wei Li, Vice President and General Manager for Machine Learning and Translation at Intel, discusses the increasing importance of AI, the vision for AI’s future benefits to humanity, and Intel’s efforts in providing an advanced platform to facilitate AI deployment from the Cloud to the edge.
Slidecast: BigDL Open Source Machine Learning Framework for Apache Spark
November 12, 2018 by Leave a Comment
In this video, Beenish Zia from Intel presents: BigDL Open Source Machine Learning Framework for Apache Spark. “BigDL is a distributed deep learning library for Apache Spark*. Using BigDL, you can write deep learning applications as Scala or Python* programs and take advantage of the power of scalable Spark clusters. This article introduces BigDL, shows you how to build the library on a variety of platforms, and provides examples of BigDL in action.”
Video: The Separation of Concerns in Code Modernization
November 7, 2018 by Leave a Comment
In this video, Larry Meadows from Intel describes why modern processors require modern coding techniques. With vectorization and threading for code modernization, you can enjoy the full potential of Intel Scalable Processors. “In many ways, code modernization is inevitable. Even EDGE devices nowadays have multiple physical cores. And even a single-core machine will have hyperthreads. And keeping those cores busy and fed with data with Intel programming tools is the best way to speed up your applications.”
Appentra Auto-parallelization coming to Emerging Technologies Showcase at SC18
November 5, 2018 by Leave a Comment
Today HPC Startup Appentra Solutions announced the company’s plans to showcase its auto-parallelization technologies at the Emerging Technologies Showcase at SC18. “SC18 is the premier international conference for High Performance Computing, networking, storage, and analysis. Every year, the Emerging Technologies program at the SC conference, showcases innovative solutions, from industry, government laboratories and academia, that may significantly improve and extend the world of HPC in the next five to fifteen years.”
Optimizing HPC Code with Roofline Analysis
October 23, 2018 by Leave a Comment
In this special guest feature, James Reinders describes why roofline estimation is a great tool for code optimization in HPC. “As a long-time teacher of optimization techniques, I can confidently say that Roofline analysis is a must-have for anyone optimizing for performance. This has not always been the case. As I will explain, today it is an important technique to draw upon when doing performance optimization.”
ExaFLOW Project takes on High-order CFD
October 15, 2018 by Leave a Comment
After three years of working on key algorithmic challenges in CFD, the European ExaFLOW Project it touting a series of industry milestones. With three flagship runs, ExaFLOW has managed to work on different specific CFD use cases which highlight the importance of their outcomes for both industry and academia. “After three years of working on key algorithmic challenges in CFD, the European ExaFLOW Project it touting a series of industry milestones. With three flagship runs, ExaFLOW has managed to work on different specific CFD use cases which highlight the importance of their outcomes for both industry and academia.”
Video: The March to Exascale
October 12, 2018 by Leave a Comment
As the trend toward exascale HPC systems continues, the complexities of optimizing parallel applications running on them increase too. Potential performance limitations can occur at the application level which relies on the MPI. While small-scale HPC systems are more forgiving of tiny MPI latencies, large systems running at scale prove much more sensitive. Small inefficiencies can snowball into significant lag.
