Compute Accelerator Forum - Codeplay SYCL and CERN GPU Update
Wednesday 8 June 2022 -
16:30
Monday 6 June 2022
Tuesday 7 June 2022
Wednesday 8 June 2022
16:30
News
-
Benjamin Morgan
(
University of Warwick (GB)
)
Graeme A Stewart
(
CERN
)
Maria Girone
(
CERN
)
Michael Bussmann
(
Helmholtz-Zentrum Dresden - Rossendorf
)
Stefan Roiser
(
CERN
)
News
Benjamin Morgan
(
University of Warwick (GB)
)
Graeme A Stewart
(
CERN
)
Maria Girone
(
CERN
)
Michael Bussmann
(
Helmholtz-Zentrum Dresden - Rossendorf
)
Stefan Roiser
(
CERN
)
16:30 - 16:35
Room: 31/3-004 - IT Amphitheatre
16:35
CERN IT GPU Infrastructure News
-
Ricardo Rocha
(
CERN
)
Ricardo Brito Da Rocha
(
CERN
)
CERN IT GPU Infrastructure News
Ricardo Rocha
(
CERN
)
Ricardo Brito Da Rocha
(
CERN
)
16:35 - 17:05
Room: 31/3-004 - IT Amphitheatre
17:05
An Introduction to using SYCL with Nvidia GPUs and beyond
-
Joe Todd
(
Codeplay
)
An Introduction to using SYCL with Nvidia GPUs and beyond
Joe Todd
(
Codeplay
)
17:05 - 17:35
Room: 31/3-004 - IT Amphitheatre
The National Laboratories in the United States, European groups including ENCCS, and the UK Exascale program are all adopting SYCL as a way to support existing and future supercomputers from different vendors including AMD, Intel, Nvidia and beyond. By using SYCL developers can widen their target architectures from a single code base. SYCL is an industry defined multiarchitecture programming interface that can be used to target multiple accelerator architectures. SYCL supports a wide range of targets using standard C++ syntax and semantics, with libraries developed using SYCL for math and neural network operations. This session will help you to understand how you can migrate your development environment from CUDA to SYCL whilst continuing to target Nvidia GPUs and retain performance. Beyond this, the same code can be run on other processors including Intel. Using nbody simulation project code written in CUDA we will show how the code is automatically translated to SYCL and then compiled using the DPC++ compiler. Furthermore we will present some performance tips and tricks to ensure you can get the best performance from your SYCL code on Nvidia GPUs.