Vectorisation and Portable Programming using OpenCL
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1 Vectorisation and Portable Programming using OpenCL Mitglied der Helmholtz-Gemeinschaft Jülich Supercomputing Centre (JSC) Andreas Beckmann, Ilya Zhukov, Willi Homberg, JSC Wolfram Schenck, FH Bielefeld Course no. 95/2017 in the trainings programme of Forschungszentrum Jülich
2 Supercomputer Systems: Dual Track Approach 20. November 2017
3 JURECA Juelich Research on Exascale Cluster Architectures General purpose cluster 2.24 Pflop/s #50 Top compute nodes Two Intel Xeon E v3 Haswell CPUs per node 2 x 12 cores, 2.5 GHz 75 compute nodes equipped with two NVIDIA K80 GPUs 2 x 4992 CUDA cores (4 visible devices per node) 2 x 24 GiB GDDR5 memory 12 visualization nodes Two Intel Xeon E v3 Haswell CPUs per node Two NVIDIA K40 GPUs per node 2 x 12 GiB GDDR5 memory 20. November 2017 Slide 3
4 JUROPA-3 Accelerated Nodes (NVIDIA Tesla K20x, Intel Xeon Phi 5110P) 20. November x K20x accelerated compute nodes 2 Intel Xeon E (Sandy Bridge-EP) eight-core processors 2.0 GHz SMT (Simultaneous Multithreading) 64 GB memory (DDR3, 1600 MHz) IB FDR HCA 2 NVIDIA Tesla K20X GPU 2688 CUDA cores 6 GB memory 4x Xeon Phi accelerated compute nodes 2 Intel Xeon E (Sandy Bridge-EP) eight-core processors 2.0 GHz SMT (Simultaneous Multithreading) 64 GB memory (DDR3, 1600 MHz) IB FDR HCA 2 Intel Xeon Phi 5110P 60 cores
5 Agenda Day 1 09:00 Welcome 09:15 Introduction to parallel computing 10:00 Login to test systems and query OpenCL capable devices 10:30 Coffee break 10:45 OpenCL programming concepts (I) 11:45 Lunch at Casino 12:45 OpenCL programming concepts (II) 13:45 Exploit OpenCL vectorisation features 14:45 Coffee break 15:00 Example: parallel reduction 20. November 2017 Slide 5
6 Agenda Day 2 9:00 Portable performance 10:30 Coffee break 10:45 Matrix multiplication (I) 11:45 Lunch at Casino 12:45 Matrix multiplication (II) 13:45 Heterogeneous multi-device programming 14:45 Coffee break 15:00 Appendix OpenCL: History & Future OpenCL compared with CUDA 20. November 2017 Slide 6
7 Acknowledgements Many previous presentations on OpenCL have been read in preparation for this course. You are encouraged to look at these: OpenCL An Introduction for HPC Programmers, ISC2011, Tim Mattson, Intel, Udeepta Bordoloi, AMD Introduction to OpenCL, Training course June 2012, George Leaver, University of Manchester OpenCL: An Introduction, Simon McIntosh-Smith, University of Bristol NVIDIA OpenCL SDK AMD Accelerated Parallel Processing SDK Intel SDK for OpenCL Applications 20. November 2017 Slide 7
8 Course test platforms OpenCL Open Computing Language Open, royalty-free standard For cross-platform, parallel programming of modern processors An Apple initiative Specified by the Khronos group Code hardware agnostic and portable (contrary to CUDA) Intended for accessing heterogeneous computational resources CPUs (Intel processors, Intel Xeon Phi coprocessors (KNC),...) GPUs (NVIDIA Fermi, Kepler, ) not available during course: AMD APUs/CPUs/GPUs, ARM SoCs, FPGAs, DSPs, November 2017 Slide 8
9 JURECA Juelich Research on Exascale Cluster Architectures General purpose cluster 2.24 Pflop/s #50 Top compute nodes Two Intel Xeon E v3 Haswell CPUs per node 2 x 12 cores, 2.5 GHz 75 compute nodes equipped with two NVIDIA K80 GPUs 2 x 4992 CUDA cores (4 visible devices per node) 2 x 24 GiB GDDR5 memory 12 visualization nodes Two Intel Xeon E v3 Haswell CPUs per node Two NVIDIA K40 GPUs per node 2 x 12 GiB GDDR5 memory 20. November 2017 Slide 9
10 JUROPA-3 JUROPA Update Prototype System Heterogeneous prototype system:60 compute nodes 52 nodes 2 Intel Xeon E (Sandy Bridge) 8-core processor, 2-2,8 GHz GB memory 4 nodes 2x Sandy Bridge, 64 GB memory 2x NVIDIA K20x GPUs (Kepler) 3,94/1,31TFLOPS SP/DP 4 nodes 2x Sandy Bridge, 64 GB memory 2x Intel Xeon Phi 5110P 2,02/1,01TFLOPS SP/DP 20. November 2017
11 20. November 2017 Slide 11
12 Exercise OpenCL_Platforms/device-query Login to all test systems (cf. Cheat Sheet on previous slide) JURECA node JUROPA-3 GPU node JUROPA-3 MIC node and query platform information to find all OpenCL capable devices copy local directory Device_Query to the remote host inspect correspondig run script and run it./run_device_query_*.sh 20. November 2017 Slide 12
13 OpenCL Architecture: Platform Model A host is connected to one or more (possibly heterogeneous) OpenCL devices A device is divided into compute units (CUs) CUs are subdivided into processing elements (PEs) 20. November 2017 Slide 13
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