scholarly journals Future High Performance Computing Capabilities: Summary Report of the Advanced Scientific Computing Advisory Committee (ASCAC) Subcommittee

2019 ◽  
Author(s):  
Keren Bergman ◽  
Tom Conte ◽  
Al Gara ◽  
Maya Gokhale ◽  
Mike Heroux ◽  
...  
Keyword(s):  
High Performance Computing ◽  
Advisory Committee ◽  
High Performance ◽  
Scientific Computing ◽  
Summary Report ◽  
Performance Computing

scholarly journals HPC resource integration into CMS Computing via HEPCloud

2019 ◽  
Vol 214 ◽  
pp. 03031
Author(s):  
Dirk Hufnagel ◽  
Burt Holzman ◽  
David Mason ◽  
Parag Mhashilkar ◽  
Steven Timm ◽  
...  
Keyword(s):  
High Performance Computing ◽  
Performance Studies ◽  
High Performance ◽  
Scientific Computing ◽  
Current Model ◽  
Scaling Up ◽  
Resource Integration ◽  
Present Experience ◽  
Performance Computing ◽  
Increased Pressure

The higher energy and luminosity from the LHC in Run 2 have put increased pressure on CMS computing resources. Extrapolating to even higher luminosities (and thus higher event complexities and trigger rates) beyond Run 3, it becomes clear that simply scaling up the the current model of CMS computing alone will become economically unfeasible. High Performance Computing (HPC) facilities, widely used in scientific computing outside of HEP, have the potential to help fill the gap. Here we describe the U.S.CMS efforts to integrate US HPC resources into CMS Computing via the HEPCloud project at Fermilab. We present advancements in our ability to use NERSC resources at scale and efforts to integrate other HPC sites as well. We present experience in the elastic use of HPC resources, quickly scaling up use when so required by CMS workflows. We also present performance studies of the CMS multi-threaded framework on both Haswell and KNL HPC resources.

scholarly journals Understanding the landscape of scientific software used on high-performance computing platforms

2020 ◽  
Vol 34 (4) ◽  
pp. 465-477
Author(s):  
A Grannan ◽  
K Sood ◽  
B Norris ◽  
A Dubey
Keyword(s):  
High Performance Computing ◽  
High Performance ◽  
Scientific Computing ◽  
Scientific Discovery ◽  
Simulation Software ◽  
Scientific Software ◽  
Survey Paper ◽  
Software Productivity ◽  
Computing Platforms ◽  
Performance Computing

Scientific discovery increasingly relies on computation through simulations, analytics, and machine and deep learning. Of these, simulations on high-performance computing (HPC) platforms have been the cornerstone of scientific computing for more than two decades. However, the development of simulation software has, in general, occurred through accretion, with a few exceptions. With an increase in scientific understanding, models have become more complex, rendering an accretion mode untenable to the point where software productivity and sustainability have become active concerns in scientific computing. In this survey paper, we examine a modest set of HPC scientific simulation applications that are already using cutting-edge HPC platforms. Several have been in existence for a decade or more. Our objective in this survey is twofold: first, to understand the landscape of scientific computing on HPC platforms in order to distill the currently scattered knowledge about software practices that have helped both developer and software productivity, and second, to understand the kind of tools and methodologies that need attention for continued productivity.

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