Performance evaluation of concurrent collections on high-performance multicore computing systems

This paper is the first extensive performance study of a recently proposed parallel programming model, called Concurrent Collections (CnC). In CnC, the programmer expresses her computation in terms of application-specific operations, partially-ordered by semantic scheduling constraints. The CnC model is well-suited to expressing asynchronous-parallel algorithms, so we evaluate CnC using two dense linear algebra algorithms in this style for execution on state-of-the-art multicore systems: (i) a recently proposed asynchronous-parallel Cholesky factorization algorithm, (ii) a novel and non-trivial "higher-level" partly-asynchronous generalized eigensolver for dense symmetric matrices. Given a well-tuned sequential BLAS, our implementations match or exceed competing multithreaded vendor-tuned codes by up to 2.6

• Type: Journal
• Year: 2010
• Where: IPPS
• Authors: Aparna Chandramowlishwaran, Kathleen Knobe, Richard W. Vuduc
• Keywords: Cholesky Factorization Algorithm, Dense Symmetric Matrices, Distributed And Parallel Computing, IPPS 2010, Semantic Scheduling Constraints