1,242 research outputs found
4.45 Pflops Astrophysical N-Body Simulation on K computer -- The Gravitational Trillion-Body Problem
As an entry for the 2012 Gordon-Bell performance prize, we report performance
results of astrophysical N-body simulations of one trillion particles performed
on the full system of K computer. This is the first gravitational trillion-body
simulation in the world. We describe the scientific motivation, the numerical
algorithm, the parallelization strategy, and the performance analysis. Unlike
many previous Gordon-Bell prize winners that used the tree algorithm for
astrophysical N-body simulations, we used the hybrid TreePM method, for similar
level of accuracy in which the short-range force is calculated by the tree
algorithm, and the long-range force is solved by the particle-mesh algorithm.
We developed a highly-tuned gravity kernel for short-range forces, and a novel
communication algorithm for long-range forces. The average performance on 24576
and 82944 nodes of K computer are 1.53 and 4.45 Pflops, which correspond to 49%
and 42% of the peak speed.Comment: 10 pages, 6 figures, Proceedings of Supercomputing 2012
(http://sc12.supercomputing.org/), Gordon Bell Prize Winner. Additional
information is http://www.ccs.tsukuba.ac.jp/CCS/eng/gbp201
N-body simulation for self-gravitating collisional systems with a new SIMD instruction set extension to the x86 architecture, Advanced Vector eXtensions
We present a high-performance N-body code for self-gravitating collisional
systems accelerated with the aid of a new SIMD instruction set extension of the
x86 architecture: Advanced Vector eXtensions (AVX), an enhanced version of the
Streaming SIMD Extensions (SSE). With one processor core of Intel Core i7-2600
processor (8 MB cache and 3.40 GHz) based on Sandy Bridge micro-architecture,
we implemented a fourth-order Hermite scheme with individual timestep scheme
(Makino and Aarseth, 1992), and achieved the performance of 20 giga floating
point number operations per second (GFLOPS) for double-precision accuracy,
which is two times and five times higher than that of the previously developed
code implemented with the SSE instructions (Nitadori et al., 2006b), and that
of a code implemented without any explicit use of SIMD instructions with the
same processor core, respectively. We have parallelized the code by using
so-called NINJA scheme (Nitadori et al., 2006a), and achieved 90 GFLOPS for a
system containing more than N = 8192 particles with 8 MPI processes on four
cores. We expect to achieve about 10 tera FLOPS (TFLOPS) for a self-gravitating
collisional system with N 105 on massively parallel systems with at most 800
cores with Sandy Bridge micro-architecture. This performance will be comparable
to that of Graphic Processing Unit (GPU) cluster systems, such as the one with
about 200 Tesla C1070 GPUs (Spurzem et al., 2010). This paper offers an
alternative to collisional N-body simulations with GRAPEs and GPUs.Comment: 14 pages, 9 figures, 3 tables, accepted for publication in New
Astronomy. The code is publicly available at
http://code.google.com/p/phantom-grape
Direct -body code on low-power embedded ARM GPUs
This work arises on the environment of the ExaNeSt project aiming at design
and development of an exascale ready supercomputer with low energy consumption
profile but able to support the most demanding scientific and technical
applications. The ExaNeSt compute unit consists of densely-packed low-power
64-bit ARM processors, embedded within Xilinx FPGA SoCs. SoC boards are
heterogeneous architecture where computing power is supplied both by CPUs and
GPUs, and are emerging as a possible low-power and low-cost alternative to
clusters based on traditional CPUs. A state-of-the-art direct -body code
suitable for astrophysical simulations has been re-engineered in order to
exploit SoC heterogeneous platforms based on ARM CPUs and embedded GPUs.
Performance tests show that embedded GPUs can be effectively used to accelerate
real-life scientific calculations, and that are promising also because of their
energy efficiency, which is a crucial design in future exascale platforms.Comment: 16 pages, 7 figures, 1 table, accepted for publication in the
Computing Conference 2019 proceeding
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