By Vijaya Ramachandran (auth.), Michael T. Heath, Abhiram Ranade, Robert S. Schreiber (eds.)
This IMA quantity in arithmetic and its functions ALGORITHMS FOR PARALLEL PROCESSING relies at the lawsuits of a workshop that used to be a vital part of the 1996-97 IMA application on "MATHEMATICS IN HIGH-PERFORMANCE COMPUTING. " The workshop introduced jointly set of rules builders from conception, combinatorics, and clinical computing. the subjects ranged over versions, linear algebra, sorting, randomization, and graph algorithms and their research. We thank Michael T. Heath of college of lllinois at Urbana (Com puter Science), Abhiram Ranade of the Indian Institute of know-how (Computer technology and Engineering), and Robert S. Schreiber of Hewlett Packard Laboratories for his or her first-class paintings in organizing the workshop and enhancing the lawsuits. We additionally take this chance to thank the nationwide technological know-how Founda tion (NSF) and the military examine workplace (ARO), whose monetary aid made the workshop attainable. A vner Friedman Robert Gulliver v PREFACE The Workshop on Algorithms for Parallel Processing used to be held on the IMA September sixteen - 20, 1996; it was once the 1st workshop of the IMA 12 months devoted to the math of excessive functionality computing. The paintings store organizers have been Abhiram Ranade of The Indian Institute of Tech nology, Bombay, Michael Heath of the collage of Illinois, and Robert Schreiber of Hewlett Packard Laboratories. Our inspiration was once to collect researchers who do cutting edge, fascinating, parallel algorithms examine on quite a lot of themes, and through sharing insights, difficulties, instruments, and strategies to benefit whatever of price from one another.
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Since the processor is less aggressive than the latest generation of processors (1 IPC at 200MHz versus 2-3 IPC at 200-400 MHz), we scaled down the values that affect the performance of the memory subsystem and the NI as well. Thus we use somewhat smaller caches and slower memory and I/O buses. The simulator provides detailed statistics about all events in hardware, as well as statistics that help identify contention in the various components of the system. Unfortunately, protocol handlers cannot be simulated since the simulator itself is not multi-threaded.
In all SVM implementations remote requests sent over a network need to be serviced. On a uniprocessor node there is little choice in this regard; the processor must be interrupted or it must somehow poll periodically. However, with SMP nodes there are a number of choices. The two basic ideas are either to dedicate a processor within the SMP to handle network requests exclusively (by polling) or to handle the requests by interrupting one of the compute processors. A dedicated processor implementation helps to avoid interrupts, which are a performance bottleneck in most systems.
The proliferation of small-scale, bus-based shared memory multiprocessors has made it very attractive to use clusters of these as scalable multiprocessors. Communication between SMPs in these clusters is performed primarily by software. An important question for these systems is whether the coherent shared address space communication abstraction provided within the SMP node can be extended effectively in software across nodes as well. Since shared virtual memory systems have been developed to provide this abstraction across uniprocessors in software, it is attractive, though non-trivial, to extend them to exploit SMP nodes effectively.
Algorithms for Parallel Processing by Vijaya Ramachandran (auth.), Michael T. Heath, Abhiram Ranade, Robert S. Schreiber (eds.)