Quantifying instruction criticality for shared memory multiprocessors
Publication
, Conference
Li, T; Lebeck, AR; Sorin, DJ
Published in: Annual ACM Symposium on Parallel Algorithms and Architectures
December 1, 2003
A model was created for determining criticality in MP systems. An algorithm was devised for computing criticality and criticality of real MP workloads was evaluated. A directed acyclic graph (DAG) model for executing: critical path and slack; mapping DAGs to multiprocessor systems and computing stack was discussed. Global slack offline was computed, but processing DAGs requires large amounts of storage and time.
Duke Scholars
Published In
Annual ACM Symposium on Parallel Algorithms and Architectures
Publication Date
December 1, 2003
Start / End Page
47 / 72
Citation
APA
Chicago
ICMJE
MLA
NLM
Li, T., Lebeck, A. R., & Sorin, D. J. (2003). Quantifying instruction criticality for shared memory multiprocessors. In Annual ACM Symposium on Parallel Algorithms and Architectures (pp. 47–72).
Li, T., A. R. Lebeck, and D. J. Sorin. “Quantifying instruction criticality for shared memory multiprocessors.” In Annual ACM Symposium on Parallel Algorithms and Architectures, 47–72, 2003.
Li T, Lebeck AR, Sorin DJ. Quantifying instruction criticality for shared memory multiprocessors. In: Annual ACM Symposium on Parallel Algorithms and Architectures. 2003. p. 47–72.
Li, T., et al. “Quantifying instruction criticality for shared memory multiprocessors.” Annual ACM Symposium on Parallel Algorithms and Architectures, 2003, pp. 47–72.
Li T, Lebeck AR, Sorin DJ. Quantifying instruction criticality for shared memory multiprocessors. Annual ACM Symposium on Parallel Algorithms and Architectures. 2003. p. 47–72.
Published In
Annual ACM Symposium on Parallel Algorithms and Architectures
Publication Date
December 1, 2003
Start / End Page
47 / 72