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Articles and news on parallel programming and code modernization

Breaking Boundaries with Data Parallel C++

“There’s a new programming language in town. Called Data Parallel C++ (DPC++), it allows developers to reuse code across diverse hardware targets—CPUs and accelerators—and perform custom tuning for a specific accelerator. DPC++ is part of oneAPI—an Intel-led initiative to create a unified programming model for cross-architecture development. Based on familiar C++ and SYCL, DPC++ is an open alternative to single-architecture proprietary approaches and helps developers create solutions that better meet specialized workload requirements.”

New Intel oneAPI DevCloud makes it easier for coders working from home

Today Intel introduced the oneAPI DevCloud to make it easier and more productive for coders currently working from home. “Developing code at home requires access to compute cycles, the latest software development tools, access across diverse hardware architectures—CPUs, GPUs, and FPGAs, and expanded storage capabilities. Through the new oneAPI DevCloud, Intel aims to provide extended access, capacity and support for oneAPI developers working from home.”

Software-defined Microarchitecture: An Arguably Terrible Idea, But Certainly Not The Worst Idea

James Mickens from Harvard University gave this talk at HiPEAC 2020. “In this presentation, I will describe some of the benefits that would emerge from a new kind of processor that aggressively exposes microarchitectural state and allows it to be programmed. Using elaborate hand gestures and cheap pleas for sympathy, I will explain why my proposals are different than prior “open microarchitecture” ideas like transport-triggered designs.”

Podcast: One Big Debate over OneAPI

In this podcast, the Radio Free HPC team looks at Intel’s oneAPI project. “The OneAPI project is a highly ambitious initiative; trying to design a single API to handle CPUs, GPUs, FPGAs, and other types of processors. In the discussion, we look under the hood and see how this might work. One thing working in Intel’s favor is that they’re using data parallel C++, which is highly compatible with CUDA – and which is probably Intel’s target with this new initiative.”

Latest Release of Intel Parallel Studio XE Delivers New Features to Boost HPC and AI Performance

Intel Parallel Studio XE is a complete software development suite that includes highly optimized compilers and math and data analytics libraries, along with comprehensive tools for performance analysis, application debugging, and parallel processing. It’s available as a download for Windows, Linux, and MacOS. “With this release, the focus is on making it easier for HPC and AI developers to deliver fast and reliable parallel code for the most demanding applications.”

New Paper Surveys Optimization Techniques for Intel Xeon Phi

A new paper by Dr Sparsh Mittal surveys techniques for evaluating and optimizing Intel’s Xeon Phi. Now accepted in Concurrency and Computation 2020, the survey reviews nearly 100 papers. “Intel Xeon Phi combines the parallel processing power of a many-core accelerator with the programming ease of CPUs. Phi has powered many supercomputers, e.g., in June 2018 list of Top500 supercomputers, 19 supercomputers used Phi as the main processing unit. This paper surveys works that study the architecture of Phi and use it as an accelerator for various applications. It critically examines the performance bottlenecks and optimization strategies for Phi. For example, the main motivation and justification for development of Phi was ease of programming.”

Video: How oneAPI Is Revolutionizing Programming

In this video, academics and industry experts weigh in on the potential of oneAPI, the new, unified software programming model for CPU, GPU, AI, and FPGA accelerators that delivers high compute performance for emerging specialized workloads across diverse compute architectures. 

Call for Papers: SCALE 2020 Scalable Computing Challenge for Cash Prizes

The IEEE International Scalable Computing Challenge (SCALE 2020) has issued its Call for Papers. “Are you doing real-world problem-solving using computing that scales? Want to win $1000 or $500? Submit a whitepaper to 13th IEEE International Scalable Computing Challenge (SCALE 2020) by Feb 5, 2020. Finalists must register, present & demo at CCGrid 2020.”

Jack Dongarra presents: Adaptive Linear Solvers and Eigensolvers

Jack Dongarra from UT Knoxville gave this talk at ATPESC 2019. “Success in large-scale scientific computations often depends on algorithm design. Even the fastest machine may prove to be inadequate if insufficient attention is paid to the way in which the computation is organized. We have used several problems from computational physics to illustrate the importance of good algorithms, and we offer some very general principles for designing algorithms.”

Appentra Releases Parallelware Trainer 1.4

Today Appentra released Parallelware Trainer 1.4, an interactive, real-time code editor with features that facilitate the learning, usage, and implementation of parallel programming by understanding how and why sections of code can be parallelized. “As Appentra strives to make parallel programming easier, enabling everyone to make the best use of parallel computing hardware from the multi-cores in a laptop to the fastest supercomputers. With this new release, we push Parallelware Trainer further towards that goal.”