Contents:
- Letter from the Editor: The Parallel Universe Turns 10 by Henry A. Gabb, Senior Principal Engineer, Intel Corporation
- GPU-Quicksort: How to Move from OpenCL™ to Data Parallel C++ by Robert Ioffe, Senior Exascale Performance Software Engineer, Intel Corporation
- Optimizing the Performance of oneAPI Applications: Getting the Most from this Unified, Standards-Based Programming Model by Kevin O’Leary, Software Technical Consulting Engineer, Intel Corporation
- Speeding Up Monte Carlo Simulation with Intel® oneMKL: Intel® oneAPI Math Kernel Library (Beta) Data Parallel C++ Usage Models by Alina Elizarova and Pavel Dyakov, Math Algorithm Engineers, and Gennady Fedorov, Software Technical Consulting Engineer, Intel Corporation
- Bringing Accelerated Analytics at Scale to Intel® Architecture: Unifying Data Science with Traditional Analytics on Modern Hardware by Venkat Krishnamurthy, Product Vice President, and Kathryn Vandiver, Senior Director, Platform and Core Engineering, OmniSci
- A New Approach to Parallel Computing Using Automatic Differentiation: Getting Top Performance on Modern Multicore Systems by Dmitri Goloubentsev, Head of Automatic Adjoint Differentiation, Matlogica, and Evgeny Lakshtanov, Principal Researcher, Department of Mathematics, University of Aveiro, Portugal and Matlogica LTD
- 8 Rules for Parallel Programming for Multicore: There are Some Consistent Rules that can Help you Solve the Parallelism Challenge and Tap Into the Potential of Multicore by James Reinders, Founding Editor and Editor Emeritus of The Parallel Universe
- Book Review: The OpenMP Common Core Making OpenMP Simple Again by Ruud van der Pas, Senior Principal Software Engineer, Oracle Corporation