By Topic

Integrating software distributed shared memory and message passing programming

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Wong, H.J. ; Dept. of Comput. Sci., Australian Nat. Univ., Canberra, ACT, Australia ; Rendell, A.P.

Software distributed shared memory (SDSM) systems provide programmers with a shared memory programming environment across distributed memory architectures. In contrast to the message passing programming environment, the SDSM can resolve data dependencies within the application without the programmer having to explicitly specify communication. However, this service is provided at a cost to performance. Thus it makes sense to use message passing directly when data dependencies are easy to solve using message passing. For example, it is not complicated to specify data transfer for large contiguous regions of memory. This paper outlines how the Danui SDSM library has been extended to include support for message passing. Four different message passing transfers are identified depending on whether the data being sent/received resides in private or globally shared buffers. Transfers between globally shared buffers are further categorized as symmetrical or asymmetrical depending on whether they correspond to the same region of shared memory. The implication of each transfer type on the memory consistency of the global address space is discussed. Central to the Danui SDSM extension is the use of information provided and implied by message passing operations. The overhead of the implementation is analyzed.

Published in:

Cluster Computing and Workshops, 2009. CLUSTER '09. IEEE International Conference on

Date of Conference:

Aug. 31 2009-Sept. 4 2009