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NAND flash memories have been used in many mobile consumer devices as storage media because they are small, fast, shock-resistant, and energy-efficient. However, the flash storage systems based on these flash devices need a special software layer, the FTL, to translate logical addresses from a host system to physical addresses in NAND flash memories. Recently, the flash storage systems in mobile devices tend to employ a page-level mapping scheme as they are required to yield higher access bandwidth. Unlike common SSDs, which often keep the majority of mapping information in fast but volatile DRAM, the flash storage systems in mobile consumer devices keep only a limited subset of mapping information in a small-sized SRAM due to the restrictions in size, cost, and power consumption. For this reason, many cache management schemes proposed for SSDs may not be suitable for the flash storage systems in mobile consumer devices, though most map cache management schemes used in mobile storage are basically designed for SSD. This paper proposes a novel cache management scheme targeting mobile consumer devices. The proposed scheme uses different management granularities in allocating and evacuating cache space. Experimental results show that the proposed scheme improves map cache performance by up to 36% compared to the existing cache management techniques.

컴퓨터의 그래픽 연산장치인 GPU는 그래픽 데이터의 연산뿐만 아니라 일반시스템 데이터를 처리할 수 있도록 발전되었으며, 3D 그래픽 관련 알고리즘이나 병렬 실행이 가능한 코드에 대해서는 CPU 보다 우수한 성능을 보여주고 있다. CPU 기반으로 제작된 일반적인 알고리즘을 GPU에서 실행하기 위해서는, GPU 시스템의 아키텍처를 이해하고 병렬처리 능력과 새로운 메모리 구조를 고려하여 코드를 재작성하여야 한다. 이를 위해서는 알고리즘을 성능 예측 모델에 적용하여 GPU 시스템에서 예상되는 성능 예측이 필수적이다. 이를 통해 GPU 기반 어플리케이션 개발에서 발생할 수 있는 문제점들을 사전에 예측하고, 성능에 대한 평가 지표를 구성할 수 있다. 본 논문에서는 AES 암호화 알고리즘에 성능예측 모델을 적용하여 작업량이 많은 조건하에서 높은 정확도로 성능 예측을 수행하였다.

NAND flash memory has been widely used as a storage medium in mobile devices, PCs, and workstations due to its advantages such as low power consumption, high performance, and random accessability compared to a hard disk drive. However, NAND flash cannot support in-place update so that it is mandatory to erase the entire block before overwriting the corresponding page. In order to overcome this drawback, flash storages need a software support, named Flash Translation Layer. However, as the high performance mass NAND flash memory is getting widely used, the size of mapping tables is increasing more than the limited DRAM size. In this paper, we propose an adaptive mapping information caching algorithm based on page mapping to solve this DRAM space shortage problem. Our algorithm uses a mapping information caching scheme which minimize the flash memory access frequency based on the analysis of several workloads. The experimental results show that the proposed algorithm can increase the performance by up to 70% comparing with the previous mapping information caching algorithm.