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DTSTART:19700308T020000
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DTSTAMP:20230124T171522Z
LOCATION:D174
DTSTART;TZID=America/Chicago:20221118T093300
DTEND;TZID=America/Chicago:20221118T100000
UID:submissions.supercomputing.org_SC22_sess450_ws_waccpd111@linklings.com
SUMMARY:Extending MAGMA Portability with OneAPI
DESCRIPTION:Workshop\n\nExtending MAGMA Portability with OneAPI\n\nFortenb
 erry, Tomov\n\nThe architectures of supercomputers are increasing in heter
 ogeneity. It is important to maintain efficient code portability to take a
 dvantage of the computing capabilities of the evolving hardware in these s
 ystems. Intel has adopted an open standard programming interface for heter
 ogeneous systems called oneAPI, designed to allow code portability across 
 different processor architectures. This paper evaluates oneAPI by porting 
 the dense linear algebra library Matrix Algebra on GPU and Multicore Archi
 tectures to Data Parallel C++, the direct programming language of oneAPI. 
 Performance of the migrated code for GEMM is compared to MKL, OpenMP GEMM 
 and native CUDA implementations on multicore CPUs and GPUs. The initial mi
 grated code demonstrates impressive performance on multicore CPUs. It also
  retains the performance of CUDA on NVIDIA GPUs. It performs poorly on the
  Intel GPU but is improved through autotuning. Intel's oneAPI allowed for 
 a successful extension of MAGMA portability to multicore CPUs and Intel GP
 Us.\n\nSession Format: Recorded\n\nTag: Accelerator-based Architectures, C
 ompilers, Dataflow and Tasking, Directive Based Programming, Heterogeneous
  Systems, Parallel Programming Languages and Models, Runtime Systems\n\nRe
 gistration Category: Workshop Reg Pass
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