Computational scientific applications tend to be very data I/O intensive, producing a large amount of data as the execution result. In this research, we propose a new storage system using next-generation non-volatile memory that is suitable for exa-scale computing systems. This storage system is called the Cloud Computing Burst System (CCBS) and is composed of a unified table management module, data scoring module, and CCBS storage. In particular, CCBS operates as a workload enlightened storage system using its own data scoring module. The CCBS storage architecture consists of PCM/NAND Flash arrays and a data migration engine. CCBS storage cannot only provide a scaling out feature, but also improve the overall performance of the storage system. In addition, by using new non-volatile memory array, many benefits, such as low energy consumption, density scaling, and high performance, can be achieved. We demonstrate the effectiveness of our proposed system by simulating the storage system using scientific benchmarking tool. Our data scoring algorithm can provide 7% more hit rate than other methods for CCBS. In addition, our proposed system has improved storage system speed by 1.64 times, compared with only NAND Flash conventional model.
All Science Journal Classification (ASJC) codes
- Theoretical Computer Science
- Information Systems
- Hardware and Architecture