STAND: New tool for performance estimation of the block data processing algorithms in high-load systems

Abstract

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.

Keywords

• Algorithms
• Performance analysis
• Block data processing
• ccNUMA