Improving STM performance with transactional structs
Ryan Yates, Michael Lee Scott
Abstract
Ryan Yates, Michael Lee Scott
Abstract
Software transactional memory (STM) has made it significantly easier to write correct concurrent programs in Haskell. Its performance, however, is limited by several inefficiencies. While safe concurrent computations are easy to express in Haskell's STM, concurrent data structures suffer unfortunate bloat in the implementation due to an extra level of indirection for mutable references as well as the inability to express unboxed mutable transactional values. We address these deficiencies by introducing TStruct to the GHC run-time system, allowing strict unboxed transactional values as well as mutable references without an extra indirection. Using TStruct we implement several data structures, discuss their design, and provide benchmark results on a large multicore machine. Our benchmarks show that concurrent data structures built with TStruct out-scale and out-perform their TVar-based equivalents.
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Software transactional memory (STM) has made it significantly easier to write correct concurrent programs in Haskell. Its performance, however, is limited by several inefficiencies. While safe concurrent computations are easy to express in Haskell's STM, concurrent data structures suffer unfortunate bloat in the implementation due to an extra level of indirection for mutable references as well as the inability to express unboxed mutable transactional values. We address these deficiencies by introducing TStruct to the GHC run-time system, allowing strict unboxed transactional values as well as mutable references without an extra indirection. Using TStruct we implement several data structures, discuss their design, and provide benchmark results on a large multicore machine. Our benchmarks show that concurrent data structures built with TStruct out-scale and out-perform their TVar-based equivalents.
Key concepts: Software transactional memory, Computer science, Indirection, Haskell, Transactional memory, Concurrent data structure, Programming language, Parallel computing