Masami Matsumoto

A problem-solving environment (PSE) for distributed computing

A problem-solving environment (PSE) for a distributed high-performance computing (HPC) is proposed to help users to work on distributed computer environment. When users access and use distributed computers for scientific computations, the PSE tells users which computers are available and appropriate for their specific application software by using hardware and software informations specified. Then, the users deploy their software on the distributed computer systems. The software, which can be used later or available for other users, is plugged and pooled in the PSE application pool in order to enhance their reusability. The problem-solving process work flow (WF) is also stored in a case-based database (DB) in the PSE and then the case DB can be used to suggest a WF for users to solve their problems. The PSE may open a new flexible HPC environment.

Visual Steering of the Simulation Process in a Scientific Numerical Simulation Environment NCAS

NCAS, an interactive problem solving environment (PSE), visualizes and steers the simulation process. Via the interactive PSE, scientists and engineers can perform a discretization of basic equations, design and generate a simulation program, perform and steer computations, and visualize the simulation results in real time. NCAS also generates a domain-decomposition parallel program using MPI functions from a mathematical model. The steering and visualization capabilities are accomplished via a tree-type data structure for equations, symbols and processes. Utilizing the NCAS system, quick responses to the user’s steering are realized and potential errors are avoided.

A meta Problem Solving Environment (PSE)

In this paper, we introduce a new framework called PSE Park for constructing a Problem Solving Environment (PSE); it enables us to construct PSEs easily. PSE Park outputs PSEs depending on users demand/input. In this sense, PSE Park is a kind of PSE for PSE, and helps users to construct PSEs. PSE Park consists of four engines: PIPE server, core, registration engine, and console. A PSE designed and constructed in PSE Park consists of several cores, which are functions of a PSE. The PIPE server manages the cores on the basis of the core map, which expresses the flow of the cores for a specific PSE. The output of each core is retrieved and merged by the PIPE server. All outputs of the cores are saved and easily reused. The cores are independent of programming languages because each core is executed individually as a process in PSE Park. They are registered by using the registration engine, and users access the engines via the console. All data including the core itself, definitions related to the core, the core map, results, and so on are stored in a distributed key-value store on the cloud computing environment. PSE Park retrieves the data by using a key name that can identify individual data uniquely. We applied PSE Park to develop the job execution PSE and the PSE for partial differential equation (PDE)-based problems. The job execution PSE helps Finite Difference Time Domain (FDTD) simulation execution. This PSE outputs the simulation results of the electric field. PDE-based PSE supports some simulation steps. Seven cores were used to construct this example PSE. By using this PSE, users can execute a PDE-based simulation and obtain a detailed document about the simulation. We believe that the concept of PSE Park, i.e., a framework for PSE development, presents a meaningful new direction for problem solving environments.

Numerical simulation for particle acceleration and trapping by an electromagnetic wave

The interaction between particles and an electromagnetic (EM) wave is investigated numerically in the system of particle V p × B acceleration by the EM wave. Numerical simulations show that the particle acceleration mechanism works well in the case of the appropriate number density of the imposed particles. When the interaction between particles and the wave is too strong, a part of the trapped and accelerated particles is detrapped. A condition is also presented for the efficient particle acceleration and trapping by the EM wave.

Focusing of intense light-ion beam by self magnetic field

This paper presents an analysis for focusing of an intense proton beam by a self-magnetic field. In this analysis, the self-magnetic field is used in a positive sense for beam focusing. The computation employs an equation for the beam trajectory in which the effect of the self-magnetic field is included. The results show that it is possible to use the self-magnetic field for the good beam focusing.