The HPC Advisory Council
held its 2017 workshop in Lugano
in the beautiful region of Ticino, Switzerland.
InsideHPC has recorded footage and gathered
presentation slides from much of the conference, available here.
I was able to attend this year, and was thoroughly delighted to do
so. The conference content included some stimulating presentations
outlining the future directions of HPC. Three general themes were
strong in much of the content.
Deep Learning & AI
It is clear that Deep Learning algorithms are transforming many
areas of scientific computing. With presentations ranging from the
giant corporations (such as IBM) to new and nimble startups (such
as DeepCube), there is huge interest and clear potential for where
Deep Learning techniques can be applied.
GPUs and Accelerators
If Deep Learning holds great promise for researchers looking for
solutions to the problems of modern science, it also holds great
promise for the bottom line of companies developing accelerators
such as GPUs and more exotic hardware architectures! The highly
computationally-intensive nature of Deep Learning algorithms was
the subject of several very interesting talks, including
refactoring software with awareness of PCI bus congestion, direct
communication between GPUs and HPC networks, and the new OpenCAPI
initiative for OpenPOWER.
OpenStack is clearly thriving in this space. DK Panda from Ohio State
University presented two
compelling keynotes describing their latest work on enhancing MVAPICH2
MPI for virtualisation and big data software stacks. Francis Lam
from Huawei talked about HPC hardware, citing OpenStack use cases.
Mike Lowe and Dave Hancock from Indiana University presented the
OpenStack journey they took with getting Jetstream into production. With
Jetstream's deployment Mike took a very hands-on approach, and as a
result they have a system that performs very well for research
computing requirements, but is also well understood by Mike and his
team at a fundamental level.
Saverio Proto from SWITCH
described how they are able to integrate cloud instances
into the layer-2 data centre networks of the research faculties they
are supporting, giving seamless scalability without any inconvenience
to the researchers using the platform.
I had the honour of the closing end note address, and I took the
opportunity to lay out our case for using OpenStack for meeting the
needs of modern research computing.
InsideHPC covered it here.
Their footage of the presentation is also available on their YouTube
An HPC conference can bring together hot technologies such as
accelerators, deep learning and virtualisation, and appraise them
in the context of HPC's long tradition of maximising the capability
of computation at scale.
An exciting time for StackHPC to be standing at this crossroads!