Papers by Daniele De Sensi
We discuss the extended parallel pattern set identified within the EU-funded project RePhrase as ... more We discuss the extended parallel pattern set identified within the EU-funded project RePhrase as a candidate pattern set to support data intensive applications targeting heterogeneous architectures. The set has been designed to include three classes of pattern, namely i) core patterns, modelling common, not necessarily data intensive parallelism exploitation patterns, usually to be used in composition; ii) high level patterns, modelling common, complex and complete parallelism exploitation patterns; and iii) building block patterns, modelling the single components of data intensive applications, suitable for use–in composition–to implement patterns not covered by the core and high level patterns. We discuss the expressive power of the RePhrase extended pattern set and results illustrating the performances that may be achieved with the FastFlow implementation of the high level patterns.
ACM Transactions on Architecture and Code Optimization, 2017
High-level parallel programming is an active research topic aimed at promoting parallel programmi... more High-level parallel programming is an active research topic aimed at promoting parallel programming methodologies that provide the programmer with high-level abstractions to develop complex parallel sooware with reduced time-to-solution. Paaern-based parallel programming is based on a set of composable and customizable parallel paaerns used as basic building blocks in parallel applications. In recent years, a considerable eeort has been made in empowering this programming model with features able to overcome shortcomings of early approaches concerning exibility and performance. In this paper we demonstrate that the approach is exible and eecient enough by applying it on 12 out of 13 PARSEC applications. Our analysis, conducted on three diierent multi-core architectures, demonstrates that paaern-based parallel programming has reached a good level of maturity, providing comparable results in terms of performance with respect to both other parallel programming methodologies based on pragma-based annotations (i.e. OOOOMP and OOOSS) and native implementations (i.e. PPPPPPPP). Regarding the programming eeort, we also demonstrate a considerable reduction in Lines-Of-Code (LOC) and Code Churn compared with PPPPPPPP and comparable results with respect to other existing implementations.
High-level parallel programming is a de-facto standard approach to develop parallel software with... more High-level parallel programming is a de-facto standard approach to develop parallel software with reduced time to development. High-level abstractions are provided by existing frameworks as pragma-based annotations in the source code, or through pre-built parallel patterns that recur frequently in parallel algorithms, and that can be easily instantiated by the programmer to add a structure to the development of parallel software. In this paper we focus on this second approach and we propose P 3 ARSEC, a benchmark suite for parallel pattern-based frameworks consisting of a representative subset of PARSEC applications. We analyse the programmability advantages and the potential performance penalty of using such high-level methodology with respect to handmade parallelisations using low-level mechanisms. The results are obtained on the new Intel Knights Landing multicore, and show a significantly reduced code complexity with comparable performance.
2016 24th Euromicro International Conference on Parallel, Distributed, and Network-Based Processing (PDP), 2016
2015 23rd Euromicro International Conference on Parallel, Distributed, and Network-Based Processing, 2015
Publications by Daniele De Sensi
Uploads
Papers by Daniele De Sensi
Publications by Daniele De Sensi