TY - JOUR
T1 - Traffic characteristics of a distributed memory system
AU - Smith, Jonathan M.
AU - Farber, David J.
N1 - Funding Information:
AURORA is a joint research effort undertaken by Bell Atlantic, Bell Communications Research, Inc., IBM T.J. Watson Research Center, Massachusetts Institute of Technology, MCI, Nynex, and the University of Pennsylvania. AURORA is sponsored as part of the NSF/DARPA Sponsored Gigabit Testbed Initiative through the Corporation for National Research Initiatives. NSF and DARPA provide funds to the University participants in AURORA. In addition, Bellcore is providing support to the Distributed Systems Laboratory through the DAWN project.
PY - 1991/9
Y1 - 1991/9
N2 - We believe that many distributed computing systems of the future will use distributed shared memory as a technique for interprocess communication. Thus, traffic generated by memory requests will be a major component of the traffic for any networks which connect nodes in such a system. In this paper, we study memory reference strings gathered with a tracing program we devised. We study several models. First, we look at raw reference data, as would be seen if the network were a backplane. Second, we examine references in units of "blocks", first using a one-block cache model and then with an infinite cache. Finally, we study the effect of predictive prepaging of these "blocks" on the traffic. We provide a novel representation of memory reference data which can used to calculate interarrival distributions directly. Integrating communication with computation can be used to control both traffic and performance.
AB - We believe that many distributed computing systems of the future will use distributed shared memory as a technique for interprocess communication. Thus, traffic generated by memory requests will be a major component of the traffic for any networks which connect nodes in such a system. In this paper, we study memory reference strings gathered with a tracing program we devised. We study several models. First, we look at raw reference data, as would be seen if the network were a backplane. Second, we examine references in units of "blocks", first using a one-block cache model and then with an infinite cache. Finally, we study the effect of predictive prepaging of these "blocks" on the traffic. We provide a novel representation of memory reference data which can used to calculate interarrival distributions directly. Integrating communication with computation can be used to control both traffic and performance.
KW - computer networks
KW - distributed computation
KW - distributed memory
KW - networking
KW - traffic characteristics
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U2 - 10.1016/0169-7552(91)90006-X
DO - 10.1016/0169-7552(91)90006-X
M3 - Article
AN - SCOPUS:0026221302
SN - 0169-7552
VL - 22
SP - 143
EP - 154
JO - Computer Networks and ISDN Systems
JF - Computer Networks and ISDN Systems
IS - 2
ER -