Data Triggered Threads — Eliminating Redundant Computation

Monday, April 11, 2011 - 10:10am


Monday, April 18, 2011
11:00 AM – 12:00 PM
Computer Science Conference Room, Harold Frank Hall Rm. 1132

HOST: Fred Chong

SPEAKER: Dean Tullsen
Computer Science and Engineering Department
UC San Diego

Title: Data Triggered Threads — Eliminating Redundant Computation

This talk will introduce a new programming/architectural execution model
for parallel threads. Unlike threads in conventional programming models,
data-triggered threads are initiated on a change to a memory location.
This enables increased parallelism and the elimination of redundant,
unnecessary computation. This talk will focus primarily on the latter.
We’ll show that 78% of all loads fetch redundant data, leading to a high
incidence of redundant computation. By expressing computation through
data-triggered threads, that computation is executed once when the data
changes, and is skipped whenever the data does not change. The set of C
SPEC benchmarks show performance speedup of up to 5.9X, and averaging 46%.

Dean Tullsen is a professor in the computer science and engineering
department at UCSD. He received his PhD from the University of
Washington in 1996, where he introduced the concept of simultaneous
multithreading (hyper-threading). He has continued to work in the area
of computer architecture and back-end compilation, where with various
co-authors he has introduced many new ideas to the research community,
including threaded multipath execution, symbiotic job scheduling for
multithreaded processors, dynamic critical path prediction, speculative
precomputation, heterogeneous multi-core architectures, conjoined core
architectures, and event-driven simultaneous code optimization. He is a
Fellow of the IEEE.