IEEE Transactions on Parallel and Distributed Systems

IEEE Transactions on Parallel and Distributed Systems (TPDS) is a scholarly archival journal published monthly. Parallelism and distributed computing are foundational research and technology to rapidly advance computer systems and their applications. Read the full scope of TPDS.


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From the May 2018 Issue

A Guide for Achieving High Performance with Very Small Matrices on GPU: A Case Study of Batched LU and Cholesky Factorizations

By Azzam Haidar, Ahmad Abdelfattah, Mawussi Zounon, Stanimire Tomov, and Jack Dongarra

Free Featured Article We present a high-performance GPU kernel with a substantial speedup over vendor libraries for very small matrix computations. In addition, we discuss most of the challenges that hinder the design of efficient GPU kernels for small matrix algorithms. We propose relevant algorithm analysis to harness the full power of a GPU, and strategies for predicting the performance, before introducing a proper implementation. We develop a theoretical analysis and a methodology for high-performance linear solvers for very small matrices. As test cases, we take the Cholesky and LU factorizations and show how the proposed methodology enables us to achieve a performance close to the theoretical upper bound of the hardware. This work investigates and proposes novel algorithms for designing highly optimized GPU kernels for solving batches of hundreds of thousands of small-size Cholesky and LU factorizations. Our focus on efficient batched Cholesky and batched LU kernels is motivated by the increasing need for these kernels in scientific simulations (e.g., astrophysics applications). Techniques for optimal memory traffic, register blocking, and tunable concurrency are incorporated in our proposed design. The proposed GPU kernels achieve performance speedups versus CUBLAS of up to 6× for the factorizations, using double precision arithmetic on an NVIDIA Pascal P100 GPU.

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Editorials and Announcements

Announcements

  • We are pleased to announce that Manish Parashar, a Distinguished Professor of Computer Science at Rutgers, The State University of New Jersey University, has been selected as the new Editor-in-Chief of the IEEE Transactions on Parallel and Distributed Systems starting in 2018.
  • We are pleased to announce that Xian-He Sun, a Distinguished Professor of Computer Science at The Illinois Institute of Technology, has been selected as the new Associate Editor-in-Chief of the IEEE Transactions on Parallel and Distributed Systems starting in 2018.
  • TPDS now offers authors access to Code Ocean. Code Ocean is a cloud-based executable research platform that allows authors to share their algorithms in an effort to make the world’s scientific code more open and reproducible. Learn more or sign up for free.
  • According to Clarivate Analytics' 2016 Journal Citation Report, TPDS has an impact factor of 4.181.

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