14.9 TFLOPS Three-Dimensional Fluid Simulation for Fusion Science with HPF on the Earth Simulator

Sakagami, H.; Murai, Hitoshi; Seo, Yoshiki; Yokokawa, M.

doi:10.1109/sc.2002.10051

Cited by 26 publications

(13 citation statements)

References 11 publications

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“…Table III). Sakagami et al [15] achieved 14.9 Tflops/512 PN with 1.7 × 10 10 grid points for a fluid simulation. (They used HPF to generate flat MPI processes.)…”

Section: Parallel Programming and Performance On The Earth Simulatormentioning

confidence: 99%

A 15.2 TFlops Simulation of Geodynamo on the Earth Simulator

Kageyama

Kameyama

Fujihara

et al.

Proceedings of the ACM/IEEE SC2004 Conference

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For realistic geodynamo simulations, one must solve the magnetohydrodynamic equations to follow time development of thermal convection motion of electrically conducting fluid in a rotating spherical shell. We have developed a new geodynamo simulation code by combining the finite difference method with the recently proposed spherical overset grid called Yin-Yang grid. We achieved performance of 15.2 Tflops (46% of theoretical peak performance) on 4096 processors of the Earth Simulator.

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“…Table III). Sakagami et al [15] achieved 14.9 Tflops/512 PN with 1.7 × 10 10 grid points for a fluid simulation. (They used HPF to generate flat MPI processes.)…”

Section: Parallel Programming and Performance On The Earth Simulatormentioning

confidence: 99%

A 15.2 TFlops Simulation of Geodynamo on the Earth Simulator

Kageyama

Kameyama

Fujihara

et al.

Proceedings of the ACM/IEEE SC2004 Conference

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show abstract

“…This was highlighted dramatically when the Japanese Earth Simulator [2] results were published [20,21,24]. The Earth Simulator, based on NEC SX-6 1 vector technology, achieves five times the LINPACK performance with almost half the number of processors of the IBM SP-based ASCI White, one of the world's most powerful supercomputers [8], built using superscalar technology.…”

Section: Introductionmentioning

confidence: 99%

Performance evaluation of the SX-6 vector architecture for scientific computations

Oliker

Canning

Carter

et al. 2004

Concurrency Computat.: Pract. Exper.

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The growing gap between sustained and peak performance for scientific applications is a well-known problem in high performance computing. The recent development of parallel vector systems offers the potential to reduce this gap for many computational science codes and deliver a substantial increase in computing capabilities. This paper examines the intranode performance of the NEC SX-6 vector processor, and compares it against the cache-based IBM Power3 and Power4 superscalar architectures, across a number of key scientific computing areas. First, we present the performance of a microbenchmark suite that examines many low-level machine characteristics. Next, we study the behavior of the NAS Parallel Benchmarks. Finally, we evaluate the performance of several scientific computing codes. Overall results demonstrate that the SX-6 achieves high performance on a large fraction of our application suite and often significantly outperforms the cache-based architectures. However, certain classes of applications are not easily amenable to vectorization and would require extensive algorithm and implementation reengineering to utilize the SX-6 effectively.

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“…This was highlighted dramatically when the Japanese Earth Simulator System's [2] results were published [18,19,22]. The Earth Simulator, based on NEC SX-6 1 vector technology, achieves five times the LINPACK performance with half the number of processors of the IBM SP-based ASCI White, the world's fourth-most powerful supercomputer [8], built using superscalar technology.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of Cache-based Superscalar and Cacheless Vector Architectures for Scientific Computations

Oliker

Canning

Carter

et al. 2003

Proceedings of the 2003 ACM/IEEE Conference on Supercomputing

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The growing gap between sustained and peak performance for scientific applications is a well-known problem in high end computing. The recent development of parallel vector systems offers the potential to bridge this gap for many computational science codes and deliver a substantial increase in computing capabilities. This paper examines the intranode performance of the NEC SX-6 vector processor and the cache-based IBM Power3/4 superscalar architectures across a number of scientific computing areas. First, we present the performance of a microbenchmark suite that examines low-level machine characteristics. Next, we study the behavior of the NAS Parallel Benchmarks. Finally, we evaluate the performance of several scientific computing codes. Results demonstrate that the SX-6 achieves high performance on a large fraction of our applications and often significantly outperforms the cache-based architectures. However, certain applications are not easily amenable to vectorization and would require extensive algorithm and implementation reengineering to utilize the SX-6 effectively.

show abstract

14.9 TFLOPS Three-Dimensional Fluid Simulation for Fusion Science with HPF on the Earth Simulator

Cited by 26 publications

References 11 publications

A 15.2 TFlops Simulation of Geodynamo on the Earth Simulator

A 15.2 TFlops Simulation of Geodynamo on the Earth Simulator

Performance evaluation of the SX-6 vector architecture for scientific computations

Evaluation of Cache-based Superscalar and Cacheless Vector Architectures for Scientific Computations

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