Campus Event Calendar
Event Entry
What and Who
Is Transactional Memory Scalable
Maurice Herlihy
Brown University
SWS Distinguished Lecture Series - Spring
Maurice Herlihy received an A.B. degree in Mathematics from Harvard
University and a Ph.D. degree in Computer Science from MIT. He has
been on the faculty at Carnegie Mellon University, and a member of the
research staff at Digital Equipment Corporation's Cambridge (MA)
Research Lab. He is now a Professor of Computer Science at Brown
University.
Prof. Herlihy's research centers on practical and theoretical aspects
of multiprocessor synchronization, with a focus on wait-free and
lock-free synchronization. His 1991 paper "Wait-Free Synchronization"
won the 2003 Dijkstra Prize in Distributed Computing, and he shared
the 2004 Goedel Prize for his 1999 paper "The Topological Structure of
Asynchronous Computation." His 1993 paper inventing Transactional
Memory recently won the 2008 ISCA influential paper award. He is a
Fellow of the ACM.
AG 1, AG 2, AG 3, AG 4, AG 5, SWS, RG1, RG2
Expert Audience
English
Note: We use this to send email in the morning.
Date, Time and Location
Wednesday, 18 June 2008
16:00
60 Minutes
E1 5
019
Saarbrücken
Abstract
While transactional memory promises to ease the task of programming
emerging multicore architectures, questions remain concerning how well
it scales to long transactions and many cores. In this talk, we
identify identify two substantial limitations in the way current
proposals handle synchronization and recovery. Synchronization is
typically based on read/write conflicts: two transactions conflict if
they access the same object (or location) and one access is a write.
Recovery is (with some exceptions) typically all-or-nothing: a
transaction either commits, and installs its changes, or aborts, and
discards its changes. We argue that read-write synchronization and
all-or-nothing recovery are not well-suited to environments with
long-lived transactions, substantial contention, or both.
We describe ongoing research on how Transactional Memory can be
extended to alleviate these obstacles to scalability. We describe how
to exploit semantic knowledge to enhance concurrency, and how a
checkpoint/continuation style of programming can support fine-grained
recovery, and a novel application of Bloom filters to detect and avoid
deadlocks.
Joint work with Eric Koskinen.
Contact
Brigitta Hansen
0681 - 9325200
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Brigitta Hansen, 06/10/2008 15:26 -- Created document.