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DTSTART:19700308T020000
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DTSTART:19701101T020000
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BEGIN:VEVENT
DTSTAMP:20211207T055339Z
LOCATION:Online
DTSTART;TZID=America/Chicago:20211114T103000
DTEND;TZID=America/Chicago:20211114T110000
UID:submissions.supercomputing.org_SC21_sess433_ws_prot104@linklings.com
SUMMARY:Measurement and Analysis of GPU-Accelerated OpenCL Computations on
  Intel GPUs
DESCRIPTION:Workshop\n\nMeasurement and Analysis of GPU-Accelerated OpenCL
  Computations on Intel GPUs\n\nCherian, Zhou, Grubisic, Meng, Mellor-Crumm
 ey\n\nIn this paper, we describe extensions to Rice University's HPCToolki
 t performance tools that support measurement and analysis of Intel's DPC++
  programming model for GPU-accelerated systems atop an implementation of t
 he industry-standard OpenCL framework for heterogeneous parallelism on Int
 el GPUs.  HPCToolkit supports three techniques for performance analysis of
  programs atop OpenCL on Intel GPUs. First, HPCToolkit supports profiling 
 and tracing of OpenCL kernels. Second, HPCToolkit supports CPU-GPU blame s
 hifting for OpenCL kernel executions---a profiling technique that can iden
 tify code that executes on one or more CPUs while GPUs are idle.   Third, 
 HPCToolkit supports fine-grained measurement, analysis, and attribution of
  OpenCL GPU kernels, including instruction counts, execution latency, and 
 SIMD waste. The paper describes these capabilities and then illustrates th
 eir application in case studies with two applications that offload computa
 tions onto Intel GPUs.\n\nTag: Online Only, Heterogeneous Systems, Perform
 ance, Productivity Tools, Software Engineering\n\nRegistration Category: W
 orkshop Reg Pass
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