Hanjun Kim Hello, my name is Hanjun Kim. I am a 5th year graduate student in the computer science department at Princeton University, and advised by Prof. David August in the Liberty Research Group. My research interests are speculative parallelization techniques on various computer architectures. Office: Computer Science Building Room 223 Email: hanjunk at cs.princeton.edu |
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Publications Scalable Speculative Parallelization on Commodity Clusters [abstract] (ACM DL, PDF)
While clusters of commodity servers and switches are the most
popular form of large-scale parallel computers, many programs are
not easily parallelized for execution upon them. In particular,
high inter-node communication cost and lack of globally shared
memory appear to make clusters suitable only for server applications
with abundant task-level parallelism and scientific applications
with regular and independent units of work. Clever use of pipeline
parallelism (DSWP), thread-level speculation (TLS), and speculative
pipeline parallelism (Spec-DSWP) can mitigate the costs of
inter-thread communication on shared memory multicore machines.
This paper presents Distributed Software Multi-threaded
Transactional memory (DSMTX), a runtime system which makes these
techniques applicable to non-shared memory clusters, allowing them
to efficiently address inter-node communication costs. Initial
results suggest that DSMTX enables efficient cluster execution of a
wider set of application types. For 11 sequential C programs
parallelized for a 4-core 32-node (128 total core) cluster without
shared memory, DSMTX achieves a geomean speedup of 49x. This
compares favorably to the 15x speedup achieved by our
implementation of TLS-only support for clusters.
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