A Hybrid Approach to Parallel Pattern Discovery in C++

Funding: EU Horizon 2020 project, TeamPlay, grant number 779882, and UK EPSRC Discovery, grant number EP/P020631/1.Parallel pattern libraries offer a strong combination of abstraction and performance. However, discovering places in sequential code where parallel patterns should be introduced is still highly non-trivial, often requiring expert manual analysis and profiling. We present a hybrid discovery technique to detect instances of parallel patterns in sequential code. This employs both static and dynamic trace-based analysis, together with hotspot detection. We evaluate our pattern discovery mechanism on a number of representative benchmarks. We evaluate the performance of the resulting parallelised benchmarks on a 24-core parallel machine.Postprin

Restoration of legacy parallelism : transforming pthreads into farm and pipeline patterns

Funding: This work was generously supported by the EU Horizon 2020 project, TeamPlay (https://www.teamplay-h2020.eu), grant number 779882, and UK EPSRC Discovery, grant number EP/P020631/1.Parallel patterns are a high-level programming paradigm that enables non-experts in parallelism to develop structured parallel programs that are maintainable, adaptive, and portable whilst achieving good performance on a variety of parallel systems. However, there still exists a large base of legacy-parallel code developed using ad-hoc methods and incorporating low-level parallel/concurrency libraries such as pthreads without any parallel patterns in the fundamental design. This code would benefit from being restructured and rewritten into pattern-based code. However, the process of rewriting the code is laborious and error-prone, due to typical concurrency and pthreading code being closely intertwined throughout the business logic of the program. In this paper, we present a new software restoration methodology, to transform legacy-parallel programs implemented using pthreads into structured farm and pipeline patterned equivalents. We demonstrate our restoration technique on a number of benchmarks, allowing the introduction of patterned farm and pipeline parallelism in the resulting code; we record improvements in cyclomatic complexity and speedups on a number of representative benchmarks.Publisher PDFPeer reviewe

A hybrid approach to parallel pattern discovery in C++

Parallel pattern libraries offer a strong combination of abstraction and performance. However, discovering places in sequential code where parallel patterns should be introduced is still highly non-trivial, often requiring expert manual analysis and profiling. We present a hybrid discovery technique to detect instances of parallel patterns in sequential code. This employs both static and dynamic trace-based analysis, together with hotspot detection. We evaluate our pattern discovery mechanism on a number of representative benchmarks. We evaluate the performance of the resulting parallelised benchmarks on a 24-core parallel machine