Is General-Purpose Many-Core Parallelism Imminent?
Uzi Vishkin, University of Maryland, BaltimoreTuesday June 18th, 10:30am, IRMACS theatre, ASB 10900.
The challenge of reinventing mainstream general-purpose computing for parallelism came into focus in 2003, once processor clock frequencies generally stopped improving. This challenge is yet to be met, particularly for applications for which run-time of a single computational task, and the productivity of its parallel programming are an issue. As mobile platforms are catching up on performance, and the vendors' field is getting crowded, competition will hopefully drive vendors to meet the challenge. I will argue that the explicit multi-threaded (XMT) on-chip platform, developed by my research team, provides the missing link in the type of heterogeneous systems needed for meeting today's opportunities and constraints. XMT can do better by order-of-magnitude over vendors' many-cores on both ease-of-programming and speedups over best serial solutions and support both claims by experimental data. For ease-of-programming teaser anecdotal data include: (i) teaching graduate material at high schools, and (ii) a joint UIUC/UMD course in which no student was able to get speedups over serial on OpenMP running on commercial SMP hardware, while their speedups on XMT were in the range 7X to 25X. For speedups, stress tests of XMT relative to state-of-the-art CPUs and GPUs for irregular fine-grained problems show speedups of up to 43X; these results assume similar silicon area and power, but much simpler algorithms. To facilitate these advantages, XMT was set up as a clean-slate design supporting the foremost theory of parallel algorithms.