No abstract

Many scientific applications running on today's supercomputers deal with increasingly large data sets and are correspondingly bottlenecked by the time it takes to read or write the data from/to the file system. We therefore undertook a study to characterize the parallel I/O performance of two of today's leading parallel supercomputers: the Columbia system at NASA Ames Research Center and the NEC SX-8 supercluster at the University of Stuttgart, Germany. On both systems, we ran a total of seven parallel I/O benchmarks, comprising five low-level benchmarks: (i) IO_Bench, (ii) MPI Tile IO, (iii) IOR (POSIX and MPI-IO), (iv) b_eff_io (five different patterns), and (v) SPIOBENCH, and two scalable synthetic compact application (SSCA) benchmarks: (a) HPCS (High Productivity Computing Systems) SSCA #3 and (b) FLASH IO (parallel HDF5). We present the results of these experiments characterizing the parallel I/O performance of these two systems.

The suitability of the next generation of high performance computing systems for petascale simulations will depend on a balance between various factors such as processor performance, memory performance, local and global network performance, and Input/Output (I/O) performance. As the supercomputing industry develops new technologies for these subsystems, achieving system balance becomes challenging. In this paper we evaluate the performance of newly introduced dual-core based SGI Altix 4700 systems (both Bandwidth and Density models) and we compare their performance with that of a single-core based SGI Altix 3700 Bx2 system. The SGI Altix 4700 Density system installed in October 2007 at NASA Ames Research Center is the largest 2048-processor single system image (SSI) system in the world. We used the High Performance Computing Challenge (HPCC) benchmark, NAS Parallel benchmarks (NPB) and five real-world applications, three from computational fluid dynamics, one from climate modeling and one from nanotechnology. Our study shows that the SGI Altix 4700 Bandwidth system performs slightly better and SGI Altix 4700 Density system performs slightly worse than the SGI Altix 3700 Bx2 up to 128 processors, while the performance of the systems is almost the same beyond 128 processors, when the communication time dominates the compute time.

Many large-scale parallel scientific and engineering applications, especially climate modeling, often run for lengthy periods and require data checkpointing periodically to save the state of the computation for a program restart. In addition, such applications need to write data to disks for post-processing, e.g., visualization. Both these scenarios involve a write-only pattern using Hierarchal Data Format (HDF) files. In this paper, we study the scalability of CXFS by HDF based Structured Adaptive Mesh Refinement (AMR) application for three different block sizes. The code used is a block-structured AMR hydrodynamics code that solves compressible, reactive hydrodynamic equations and characterizes physics and mathematical algorithms used in studying nuclear flashes on neutron stars and white dwarfs. The computational domain is divided into blocks distributed across the processors. Typically, a block contains 8 zones in each coordinate direction (x, y, and z) and a perimeter of guard cells (in this case, 4 zones deep) to hold information from the neighbors. We used three different block sizes of 8 × 8 × 8, 16 × 16 × 16, and 32 × 32 × 32. Results of parallel I/O bandwidths (checkpoint file and two plot files) are presented for all three-block sizes on a wide range of processor counts, ranging from 1 to 508 processors of the Columbia system.

The Columbia project at NASA Ames includes twenty 512 processor Altix systems. Four of those systems are joined together into a Numalink based globally accessible non-coherent memory Altix SuperCluster. PBSPro 7.0 and 7.1 have been used to schedule and run work on this system. In this presentation, we will go over features of PBSPro especially applicable to such systems, some problems we have encountered and how they have been addressed, and remaining, unresolved issues.