Gyrokinetic particle simulation model
Journal of Computational Physics
Parallel empirical pseudopotential electronic structure calculations for million atom systems
Journal of Computational Physics
Scientific Computations on Modern Parallel Vector Systems
Proceedings of the 2004 ACM/IEEE conference on Supercomputing
Proceedings of the 2004 ACM/IEEE conference on Supercomputing
Early Evaluation of the Cray X1
Proceedings of the 2003 ACM/IEEE conference on Supercomputing
Hardware system of the earth simulator
Parallel Computing
Concurrency and Computation: Practice & Experience
Leading Computational Methods on Scalar and Vector HEC Platforms
SC '05 Proceedings of the 2005 ACM/IEEE conference on Supercomputing
The HPC Challenge (HPCC) benchmark suite
Proceedings of the 2006 ACM/IEEE conference on Supercomputing
Performance evaluation of supercomputers using HPCC and IMB benchmarks
IPDPS'06 Proceedings of the 20th international conference on Parallel and distributed processing
Early evaluation of the cray XT3
IPDPS'06 Proceedings of the 20th international conference on Parallel and distributed processing
Network bandwidth measurements and ratio analysis with the HPC challenge benchmark suite (HPCC)
PVM/MPI'05 Proceedings of the 12th European PVM/MPI users' group conference on Recent Advances in Parallel Virtual Machine and Message Passing Interface
Optimization of a Computational Fluid Dynamics Code for the Memory Hierarchy: A Case Study
International Journal of High Performance Computing Applications
High-performance Computing to Simulate Large-scale Industrial Flows in Multistage Compressors
International Journal of High Performance Computing Applications
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The last decade has witnessed a rapid proliferation of superscalar cache-based microprocessors to build high-end computing (HEC) platforms, primarily because of their generality, scalability, and cost effectiveness. However, the growing gap between sustained and peak performance for full-scale scientific applications on conventional supercomputers has become a major concern in high performance computing, requiring significantly larger systems and application scalability than implied by peak performance in order to achieve desired performance. The latest generation of custom-built parallel vector systems have the potential to address this issue for numerical algorithms with sufficient regularity in their computational structure. In this work we explore applications drawn from four areas: magnetic fusion (GTC), plasma physics (LB-MHD-3D), astrophysics (Cactus), and material science (PARATEC). We compare performance of the vector-based Cray X1, X1E, Earth Simulator, NEC SX-8, with performance of three leading commodity-based super-scalar platforms utilizing the IBM Power3, Intel Itanium2, and AMD Opteron processors. Our work makes several significant contributions: a new data-decomposition scheme for GTC that (for the first time) enables a breakthrough of the teraflop barrier; the introduction of a new three-dimensional lattice Boltzmann magneto-hydrodynamic implementation used to study the onset evolution of plasma turbulence that achieves over 26 Tflop/s on 4800 ES processors; the highest per processor performance (by far) achieved by the full-production version of the Cactus ADM-BSSN; and the largest PARATEC cell size atomistic simulation to date. Overall, results show that the vector architectures attain unprecedented aggregate performance across our application suite, demonstrating the tremendous potential of modern parallel vector systems.