Hardware MultiThreaded Transactions: Enabling Speculative MultiThreaded Pipeline Parallelization For Complex Programs [abstract] (PDF)
Jordan Fix
Ph.D. Thesis, Department of Computer Science,
Princeton University, 2020.
Speculation with transactional memory systems helps programmers and compilers produce profitable thread-level parallel programs. Prior work shows that supporting transactions that can span multiple threads, rather than requiring transactions be contained within
a single thread, enables new types of speculative parallelization techniques for both programmers and parallelizing compilers.
Unfortunately, software support for multi-threaded transactions (MTXs) comes with
significant additional inter-thread communication overhead for speculation validation. This
overhead can make otherwise good parallelization unprofitable for programs with sizeable
read and write sets.
Some programs using these prior software MTXs overcame this problem through significant efforts by expert programmers to minimize these sets and optimize communication, capabilities which compiler technology has been unable to achieve to date. Instead,
this dissertation makes speculative parallelization less laborious and more feasible through
low-overhead speculation validation, presenting the first complete design, implementation,
and evaluation of hardware MTXs.
Even with maximal speculation validation of every load and store inside transactions of
tens to hundreds of millions of instructions, profitable parallelization of complex programs
can be achieved. Across 8 benchmarks, this system achieves a geomean speedup of 104%
over sequential execution on a multicore machine with 4 cores, with modest increases in
power and energy consumption. This work could be used as a building block to enable
more realistic automatic parallelization of complex programs, by providing low-overhead,
long-running, resilient transactions that support a diverse set of parallel paradigm options.