In recent years, programming high performance computing systems has
shifted from single layer programming models to multiple layers of
massively parallel systems. Widely used message-passing or thread
programming models do not longer map efficiently to upcoming
heterogeneous systems. Further, different brands of graphics cards
(GPU) and accelerators, as well as large numbers of processor (CPU)
cores, each with increasing vector computing capability require
dedicated computational kernels. However, topics like code
optimization and portable code development remain
challenging.
This workshop will focus on aspects of heterogeneous computing
systems. This includes GPU computing, accelerators offloading,
vector instruction sets and the multi level hierarchy of distributed
and shared memory resources found in large scale computing.
The first day of the workshop is dedicated to an introduction
to programming aspects. A tutorial including a hands-on session will
give the opportunity for less experienced participants to learn about
GPU computing.
The next day of the workshop will discuss how
physics applications, especially in relativity and quantum field
theory, may benefit from the use of accelerators. The topics covered by this
workshops are:
Abstracts should be submitted by end of April 2014 through the registration page.
The workshop is organized by
B. Brügmann (University Jena)
X. Cai (Simula and University Oslo)
G. Haase (University Graz)
G. Zumbusch (Chair, University Jena)
This workshop is supported by
German Research Foundation | SFB/TR 7 | GK 1523 | Master Computational and Data Science |