Real space DFT (RSDFT) is a simulation technique most suitable for massively-parallel architectures to perform first-principles electronic-structure calculations based on density functional theory. We here report unprecedented simulations on the electron states of silicon nanowires with up to 107,292 atoms carried out during the initial performance evaluation phase of the K computer being developed at RIKEN.

Emerging 64bitOS’s supply a huge amount of memory address space that is essential for new applications using very large data. It is expected that the memory in connected nodes can be used to store swapped pages efficiently, especially in a dedicated cluster which has a high-speed network such as 10GbE and Infiniband. In this paper, we propose the Distributed Large Memory System (DLM), which provides very large virtual memory by using remote memory distributed over the nodes in a cluster. The performance of DLM programs using remote memory is compared to ordinary programs using local memory. The results of STREAM, NPB and Himeno benchmarks show that the DLM achieves better performance than other remote paging schemes using a block swap device to access remote memory. In addition to performance, DLM offers the advantages of easy availability and high portability, because it is a user-level software without the need for special hardware. To obtain high performance, the DLM can tune its parameters independently from kernel swap parameters. We also found that DLM’s independence of kernel swapping provides more stable behavior.

To predict application performance on an HPC system is an important technology for designing the computing system and developing applications. However, accurate prediction is a challenge, particularly, in the case of a future coming system with higher performance. In this paper, we present a new method for predicting application performance on HPC systems. This method combines modeling of sequential performance on a single processor and macro-level simulations of applications for parallel performance on the entire system. In the simulation, the execution flow is traced but kernel computations are omitted for reducing the execution time. Validation on a real terascale system showed that the predicted and measured performance agreed within 10% to 20 %. We employed the method in designing a hypothetical petascale system of 32768 SIMD-extended processor cores. For predicting application performance on the petascale system, the macro-level simulation required several hours.

The RIKEN Super Combined Cluster (RSCC) System in RIKEN Wako Inst., started its operation in March, 2004. A Web portal system called Bio Portal was developed to utilize a Linux cluster (a part of RSCC) for data analysis in the life sciences. A small SMP server was then placed in RIKEN Yokohama Inst., for small analysis, and the Bio Portal integrates both RSCC and this SMP server through the application of Grid technology. The aim of this portal system was to construct a simple data analysis environment for experimental researchers, and to improve performance of data analysis through the use of two differently performing computing resources. In this paper, we describe the Web interface and functions of Bio Portal in detail. Later we explain RSCC, and discuss performance evaluations of the distribution patterns for BLAST jobs. Finally, we propose bio informatics job distribution patterns for high throughput processing.