20,464 research outputs found
BOSS-LDG: A Novel Computational Framework that Brings Together Blue Waters, Open Science Grid, Shifter and the LIGO Data Grid to Accelerate Gravitational Wave Discovery
We present a novel computational framework that connects Blue Waters, the
NSF-supported, leadership-class supercomputer operated by NCSA, to the Laser
Interferometer Gravitational-Wave Observatory (LIGO) Data Grid via Open Science
Grid technology. To enable this computational infrastructure, we configured,
for the first time, a LIGO Data Grid Tier-1 Center that can submit
heterogeneous LIGO workflows using Open Science Grid facilities. In order to
enable a seamless connection between the LIGO Data Grid and Blue Waters via
Open Science Grid, we utilize Shifter to containerize LIGO's workflow software.
This work represents the first time Open Science Grid, Shifter, and Blue Waters
are unified to tackle a scientific problem and, in particular, it is the first
time a framework of this nature is used in the context of large scale
gravitational wave data analysis. This new framework has been used in the last
several weeks of LIGO's second discovery campaign to run the most
computationally demanding gravitational wave search workflows on Blue Waters,
and accelerate discovery in the emergent field of gravitational wave
astrophysics. We discuss the implications of this novel framework for a wider
ecosystem of Higher Performance Computing users.Comment: 10 pages, 10 figures. Accepted as a Full Research Paper to the 13th
IEEE International Conference on eScienc
Cactus: Issues for Sustainable Simulation Software
The Cactus Framework is an open-source, modular, portable programming
environment for the collaborative development and deployment of scientific
applications using high-performance computing. Its roots reach back to 1996 at
the National Center for Supercomputer Applications and the Albert Einstein
Institute in Germany, where its development jumpstarted. Since then, the Cactus
framework has witnessed major changes in hardware infrastructure as well as its
own community. This paper describes its endurance through these past changes
and, drawing upon lessons from its past, also discusses futureComment: submitted to the Workshop on Sustainable Software for Science:
Practice and Experiences 201
From Physics Model to Results: An Optimizing Framework for Cross-Architecture Code Generation
Starting from a high-level problem description in terms of partial
differential equations using abstract tensor notation, the Chemora framework
discretizes, optimizes, and generates complete high performance codes for a
wide range of compute architectures. Chemora extends the capabilities of
Cactus, facilitating the usage of large-scale CPU/GPU systems in an efficient
manner for complex applications, without low-level code tuning. Chemora
achieves parallelism through MPI and multi-threading, combining OpenMP and
CUDA. Optimizations include high-level code transformations, efficient loop
traversal strategies, dynamically selected data and instruction cache usage
strategies, and JIT compilation of GPU code tailored to the problem
characteristics. The discretization is based on higher-order finite differences
on multi-block domains. Chemora's capabilities are demonstrated by simulations
of black hole collisions. This problem provides an acid test of the framework,
as the Einstein equations contain hundreds of variables and thousands of terms.Comment: 18 pages, 4 figures, accepted for publication in Scientific
Programmin
From Tensor Equations to Numerical Code -- Computer Algebra Tools for Numerical Relativity
In this paper we present our recent work in developing a computer-algebra
tool for systems of partial differential equations (PDEs), termed "Kranc". Our
work is motivated by the problem of finding solutions of the Einstein equations
through numerical simulations. Kranc consists of Mathematica based
computer-algebra packages, that facilitate the task of dealing with symbolic
tensorial calculations and realize the conversion of systems of partial
differential evolution equations into parallelized C or Fortran code.Comment: LaTeX llncs style, 9 pages, 1 figure, to appaer in the proceedings of
"SYNASC 2004 - 6th International Symposium on Symbolic and Numeric Algorithms
for Scientific Computing", Timisoara, Romania, September 26-30 200
An Extensible Timing Infrastructure for Adaptive Large-scale Applications
Real-time access to accurate and reliable timing information is necessary to
profile scientific applications, and crucial as simulations become increasingly
complex, adaptive, and large-scale. The Cactus Framework provides flexible and
extensible capabilities for timing information through a well designed
infrastructure and timing API. Applications built with Cactus automatically
gain access to built-in timers, such as gettimeofday and getrusage,
system-specific hardware clocks, and high-level interfaces such as PAPI. We
describe the Cactus timer interface, its motivation, and its implementation. We
then demonstrate how this timing information can be used by an example
scientific application to profile itself, and to dynamically adapt itself to a
changing environment at run time
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