STAND: New Tool for Performance Estimation of the Block Data Processing Algorithms in High-load Systems

被引:0
作者
Minchenkov, Victor [1 ]
Bashun, Vladimir [1 ]
Povalyaev, Alexander [2 ]
机构
[1] St Petersburg State Univ Aerosp Instrumentat, St Petersburg, Russia
[2] EMC St Petersburg Dev Ctr, St Petersburg, Russia
来源
PROCEEDINGS OF THE 2013 13TH CONFERENCE OF OPEN INNOVATIONS ASSOCIATION (FRUCT) | 2013年
关键词
Algorithms; Performance analysis; Block data processing; ccNUMA;
D O I
暂无
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
The main goal of this work is to present the developed research tool to find, investigate and analyze hidden dependences between parameters of the hardware/software platforms (such as influence of NUMA architecture, memory page size, etc) and the performance of block data processing algorithms. The new toolset (STAND) allows performance estimation and comparison of block data processing algorithms (for example, encryption/compression algorithms) running in kernel space. The primary application area of the developed technology and toolset is performance estimation and comparison of "black box" libraries on particular hardware/software platform rather than research of mathematical or software implementation of algorithms. The main advantage of the presented toolset is that no source codes of algorithm implementation are needed (providing that an abstraction layer with known API is available). Linux operating system and computing nodes with ccNUMA architecture was selected as basic software/hardware platform. In this paper, the architecture of STAND is described. The methods for generating system load and comparison results for encryption algorithms AES (CBC), AES (CTR), and compression algorithms LZO, quicklz and bCodec are also presented.
引用
收藏
页码:101 / 110
页数:10
相关论文
共 4 条
  • [1] [Anonymous], LOCAL REMOTE MEMORY
  • [2] Kayi Abdullah, 2008, COMPUTATIONAL SCI EN
  • [3] Panourgias I., 2011, NUMA effects on multicore, multi socket systems
  • [4] Patterson David A., 2013, Computer Organization and Design, VFifth