14,228 research outputs found
Tackling Exascale Software Challenges in Molecular Dynamics Simulations with GROMACS
GROMACS is a widely used package for biomolecular simulation, and over the
last two decades it has evolved from small-scale efficiency to advanced
heterogeneous acceleration and multi-level parallelism targeting some of the
largest supercomputers in the world. Here, we describe some of the ways we have
been able to realize this through the use of parallelization on all levels,
combined with a constant focus on absolute performance. Release 4.6 of GROMACS
uses SIMD acceleration on a wide range of architectures, GPU offloading
acceleration, and both OpenMP and MPI parallelism within and between nodes,
respectively. The recent work on acceleration made it necessary to revisit the
fundamental algorithms of molecular simulation, including the concept of
neighborsearching, and we discuss the present and future challenges we see for
exascale simulation - in particular a very fine-grained task parallelism. We
also discuss the software management, code peer review and continuous
integration testing required for a project of this complexity.Comment: EASC 2014 conference proceedin
Programming MPSoC platforms: Road works ahead
This paper summarizes a special session on multicore/multi-processor system-on-chip (MPSoC) programming challenges. The current trend towards MPSoC platforms in most computing domains does not only mean a radical change in computer architecture. Even more important from a SW developer´s viewpoint, at the same time the classical sequential von Neumann programming model needs to be overcome. Efficient utilization of the MPSoC HW resources demands for radically new models and corresponding SW development tools, capable of exploiting the available parallelism and guaranteeing bug-free parallel SW. While several standards are established in the high-performance computing domain (e.g. OpenMP), it is clear that more innovations are required for successful\ud
deployment of heterogeneous embedded MPSoC. On the other hand, at least for coming years, the freedom for disruptive programming technologies is limited by the huge amount of certified sequential code that demands for a more pragmatic, gradual tool and code replacement strategy
Domain-Specific Acceleration and Auto-Parallelization of Legacy Scientific Code in FORTRAN 77 using Source-to-Source Compilation
Massively parallel accelerators such as GPGPUs, manycores and FPGAs represent
a powerful and affordable tool for scientists who look to speed up simulations
of complex systems. However, porting code to such devices requires a detailed
understanding of heterogeneous programming tools and effective strategies for
parallelization. In this paper we present a source to source compilation
approach with whole-program analysis to automatically transform single-threaded
FORTRAN 77 legacy code into OpenCL-accelerated programs with parallelized
kernels.
The main contributions of our work are: (1) whole-source refactoring to allow
any subroutine in the code to be offloaded to an accelerator. (2) Minimization
of the data transfer between the host and the accelerator by eliminating
redundant transfers. (3) Pragmatic auto-parallelization of the code to be
offloaded to the accelerator by identification of parallelizable maps and
reductions.
We have validated the code transformation performance of the compiler on the
NIST FORTRAN 78 test suite and several real-world codes: the Large Eddy
Simulator for Urban Flows, a high-resolution turbulent flow model; the shallow
water component of the ocean model Gmodel; the Linear Baroclinic Model, an
atmospheric climate model and Flexpart-WRF, a particle dispersion simulator.
The automatic parallelization component has been tested on as 2-D Shallow
Water model (2DSW) and on the Large Eddy Simulator for Urban Flows (UFLES) and
produces a complete OpenCL-enabled code base. The fully OpenCL-accelerated
versions of the 2DSW and the UFLES are resp. 9x and 20x faster on GPU than the
original code on CPU, in both cases this is the same performance as manually
ported code.Comment: 12 pages, 5 figures, submitted to "Computers and Fluids" as full
paper from ParCFD conference entr
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