The performance impact of flexibility in the Stanford FLASH multiprocessor

  • Authors:

  • Mark Heinrich;Jeffrey Kuskin;David Ofelt;John Heinlein;Joel Baxter;Jaswinder Pal Singh;Richard Simoni;Kourosh Gharachorloo;David Nakahira;Mark Horowitz;Anoop Gupta;Mendel Rosenblum;John Hennessy

  • Affiliations:

  • Computer Systems Laboratory, Stanford University, Stanford, CA;Computer Systems Laboratory, Stanford University, Stanford, CA;Computer Systems Laboratory, Stanford University, Stanford, CA;Computer Systems Laboratory, Stanford University, Stanford, CA;Computer Systems Laboratory, Stanford University, Stanford, CA;Computer Systems Laboratory, Stanford University, Stanford, CA;Computer Systems Laboratory, Stanford University, Stanford, CA;Computer Systems Laboratory, Stanford University, Stanford, CA;Computer Systems Laboratory, Stanford University, Stanford, CA;Computer Systems Laboratory, Stanford University, Stanford, CA;Computer Systems Laboratory, Stanford University, Stanford, CA;Computer Systems Laboratory, Stanford University, Stanford, CA;Computer Systems Laboratory, Stanford University, Stanford, CA

  • Venue:
  • ASPLOS VI Proceedings of the sixth international conference on Architectural support for programming languages and operating systems
  • Year:
  • 1994

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Abstract

A flexible communication mechanism is a desirable feature in multiprocessors because it allows support for multiple communication protocols, expands performance monitoring capabilities, and leads to a simpler design and debug process. In the Stanford FLASH multiprocessor, flexibility is obtained by requiring all transactions in a node to pass through a programmable node controller, called MAGIC. In this paper, we evaluate the performance costs of flexibility by comparing the performance of FLASH to that of an idealized hardwired machine on representative parallel applications and a multiprogramming workload. To measure the performance of FLASH, we use a detailed simulator of the FLASH and MAGIC designs, together with the code sequences that implement the cache-coherence protocol. We find that for a range of optimized parallel applications the performance differences between the idealized machine and FLASH are small. For these programs, either the miss rates are small or the latency of the programmable protocol can be hidden behind the memory access time. For applications that incur a large number of remote misses or exhibit substantial hot-spotting, performance is poor for both machines, though the increased remote access latencies or the occupancy of MAGIC lead to lower performance for the flexible design. In most cases, however, FLASH is only 2%–12% slower than the idealized machine.