DeepComp: towards a balanced system design for high performance computer systems

  • Authors:

  • Mingfa Zhu;Limin Xiao;Li Ruan;Qinfen Hao

  • Affiliations:

  • State Key Laboratory of Software Development Environment, Beijing, China 100191 and School of Computer Science and Engineering, Beihang University, Beijing, China 100191;State Key Laboratory of Software Development Environment, Beijing, China 100191 and School of Computer Science and Engineering, Beihang University, Beijing, China 100191;School of Computer Science and Engineering, Beihang University, Beijing, China 100191;School of Computer Science and Engineering, Beihang University, Beijing, China 100191

  • Venue:
  • Frontiers of Computer Science in China
  • Year:
  • 2010

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Abstract

Today, cluster-based computing is the mainstream architecture for high end computer systems. Balanced system design is critical for large scale cluster systems to achieve high efficiency. This paper addresses the practice on DeepComp high end computer systems toward a balanced system design. Methodologies of designing balanced large scale cluster systems are given. A method for balancing central processing unit (CPU) and memory hierarchy is addressed. For balancing computing nodes and I/O systems, two approaches are given: maximum bandwidth criterion and maximum number of computing nodes which can concurrently access I/O systems. Experiences of Lenovo high end cluster systems show that above methods are effective. Lenovo strategies toward a balanced system design for both peta and 10 peta scale high productivity computing systems (HPCSs).