Authors: Shajulin Benedict
Addresses: Indian Institute of Information Technology Kottayam, Kerala, India
Abstract: Intel's recent manycore processor KNights Landing (KNL) promises high performance for scientific applications. Careful tuning for the complex chip architecture is required to efficiently exploit the chip's hardware resources. This paper describes performance improvement techniques and demonstrates their effectiveness for scientific applications. Experiments were conducted with some of the National Aeronautics and Space Administration (NASA's) advanced supercomputing (NAS) parallel benchmarks, and the effectiveness of: 1) advanced vector extensions (AVX-512) vectorisation support; 2) manycore threading support; 3) the utilisation of thread affinities for different KNL modes, was analysed.
Keywords: knights landing; performance analysis; performance tuning; scientific applications.
International Journal of Knowledge Engineering and Data Mining, 2018 Vol.5 No.1/2, pp.1 - 16
Received: 03 Apr 2018
Accepted: 09 Apr 2018
Published online: 19 Jun 2018 *