Hyun-Moon Park

A Development of Energy Storage Monitoring System Architecture for Triboelectric Nanogenerator in the Implant Environment

In 2012, a new energy capturing method called TENG was suggested for energy harvesting applications. The TENG which captures electric energy in forms of friction or vibration has been researched as a new energy harvesting generation device. However, TENG works on rather high voltage and yields relatively low current, and this requires additional energy conversion and saving methods with either in semiconductive elements or circuitry for its application. Irregular generation from vibration sources rattle under 5Hz especially requires empirical studies. In this article, we suggest a electricity generation platform with energy storage methods. The platform is mounted on large sized animals, and the generation is actively monitored and controlled via Bluetooth-Low Energy to verify the platform.

A Development of Fusion Processor Architecture for Efficient Main Memory Access in CPU-GPU Environment

The HSA resolves an old problem with existing CPU and GPU architectures by allowing both units to directly access each other`s memory pools via unified virtual memory. In a physically realized system, however, frequent data exchanges between CPU and GPU for a virtual memory block result bottlenecks and coherence request overheads. In this paper, we propose Fusion Processor Architecture for efficient access of main memory from both CPU and GPU. It consists of Job Manager, Re-mapper, and Pre-fetcher to control, organize, and distribute work loads and working areas for GPU cores. These components help on reducing memory exchanges between the two processors and improving overall efficiency by eliminating faulty page table requests. To verify proposed algorithm architectures, we develop an emulator based on QEMU, and compare several architectures such as CUDA(Compute Unified Device Architecture), OpenMP, OpenCL. As a result, Proposed fusion processor architectures show 198% faster than others by removing unnecessary memory copies and cache-miss overheads.

Implementation of Integrated CPU-GPU for Efficient Uniform Memory Access Method and Verification System

In this paper, we propose a system for efficient use of shared memory between CPU and GPU. The system, called Fusion Architecture, assures consistency of the shared memory and minimizes cache misses that frequently occurs on Heterogeneous System Architecture or Unified Virtual Memory based systems. It also maximizes the performance for memory intensive jobs by efficient allocation of GPU cores. To test between architectures on various scenarios, we introduce the Fusion Architecture Analyzer, which compares OpenMP, OpenCL, CUDA, and the proposed architecture in terms of memory overhead and process time. As a result, Proposed fusion architectures show that the Fusion Architecture runs benchmarks 55% faster and reduces memory overheads by 220% in average.