In recent years, the limits of the multicore approach emerged in the so-called “dark silicon”
issue and diminishing returns of an ever-increasing core count. Hardware manufacturers …

The Single Instruction Multiple Data (SIMD) architecture, supported by various high-
performance computing platforms, efficiently utilizes data-level parallelism. The SIMD model …

VPIC is a general purpose particle-in-cell simulation code for modeling plasma phenomena
such as magnetic reconnection, fusion, solar weather, and laser-plasma interaction in three …

Sparse Matrix-Vector multiplication (SpMV) is an essential kernel for parallel numerical
applications. SpMV displays sparse and irregular data accesses, which complicate its …

Data movement is a key bottleneck in terms of both performance and energy efficiency in
modern HPC systems. The NEC SX-series supercomputers have a long history of …

The Sparse GEneral Matrix-Matrix multiplication (SpGEMM) C= A x B is a fundamental
routine extensively used in domains like machine learning or graph analytics. Despite its …

Recently, a clustering method using a combinatorial optimization problem, called
combinatorial clustering, has been drawing attention due to the rapid spreads of quantum …

The performance of recent computing systems has drastically improved due to the increase
in the number of cores. However, this approach is reaching the limitation due to the power …

As robots increasingly permeate modern society, it is crucial for the system and hardware
research community to bridge its long-standing gap with robotics. This divide has persisted …

NEC SX-series vector supercomputers have provided outstanding memory bandwidths to
meet the strong demands for efficient execution of memory-intensive scientific applications …