TY - JOUR
T1 - ACOTES project: Advanced compiler technologies for embedded streaming
AU - Munk, Harm
AU - Ayguadé, Eduard
AU - Bastoul, Cédric
AU - Carpenter, Paul
AU - Chamski, Zbigniew
AU - Cohen, Albert
AU - Cornero, Marco
AU - Dumont, Philippe
AU - Duranton, Marc
AU - Fellahi, Mohammed
AU - Ferrer, Roger
AU - Ladelsky, Razya
AU - Lindwer, Menno
AU - Martorell, Xavier
AU - Miranda, Cupertino
AU - Nuzman, Dorit
AU - Ornstein, Andrea
AU - Pop, Antoniu
AU - Pop, Sebastian
AU - Pouchet, Louis Noël
AU - Ramírez, Alex
AU - Ródenas, David
AU - Rohou, Erven
AU - Rosen, Ira
AU - Shvadron, Uzi
AU - Trifunović, Konrad
AU - Zaks, Ayal
PY - 2011/6
Y1 - 2011/6
N2 - Streaming applications are built of data-driven, computational components, consuming and producing unbounded data streams. Streaming oriented systems have become dominant in a wide range of domains, including embedded applications and DSPs. However, programming efficiently for streaming architectures is a challenging task, having to carefully partition the computation and map it to processes in a way that best matches the underlying streaming architecture, taking into account the distributed resources (memory, processing, real-time requirements) and communication overheads (processing and delay). These challenges have led to a number of suggested solutions, whose goal is to improve the programmer's productivity in developing applications that process massive streams of data on programmable, parallel embedded architectures. StreamIt is one such example. Another more recent approach is that developed by the ACOTES project (Advanced Compiler Technologies for Embedded Streaming). The ACOTES approach for streaming applications consists of compiler-assisted mapping of streaming tasks to highly parallel systems in order to maximize cost-effectiveness, both in terms of energy and in terms of design effort. The analysis and transformation techniques automate large parts of the partitioning and mapping process, based on the properties of the application domain, on the quantitative information about the target systems, and on programmer directives. This paper presents the outcomes of the ACOTES project, a 3-year collaborative work of industrial (NXP, ST, IBM, Silicon Hive, NOKIA) and academic (UPC, INRIA, MINES ParisTech) partners, and advocates the use of Advanced Compiler Technologies that we developed to support Embedded Streaming. © 2010 Springer Science+Business Media, LLC.
AB - Streaming applications are built of data-driven, computational components, consuming and producing unbounded data streams. Streaming oriented systems have become dominant in a wide range of domains, including embedded applications and DSPs. However, programming efficiently for streaming architectures is a challenging task, having to carefully partition the computation and map it to processes in a way that best matches the underlying streaming architecture, taking into account the distributed resources (memory, processing, real-time requirements) and communication overheads (processing and delay). These challenges have led to a number of suggested solutions, whose goal is to improve the programmer's productivity in developing applications that process massive streams of data on programmable, parallel embedded architectures. StreamIt is one such example. Another more recent approach is that developed by the ACOTES project (Advanced Compiler Technologies for Embedded Streaming). The ACOTES approach for streaming applications consists of compiler-assisted mapping of streaming tasks to highly parallel systems in order to maximize cost-effectiveness, both in terms of energy and in terms of design effort. The analysis and transformation techniques automate large parts of the partitioning and mapping process, based on the properties of the application domain, on the quantitative information about the target systems, and on programmer directives. This paper presents the outcomes of the ACOTES project, a 3-year collaborative work of industrial (NXP, ST, IBM, Silicon Hive, NOKIA) and academic (UPC, INRIA, MINES ParisTech) partners, and advocates the use of Advanced Compiler Technologies that we developed to support Embedded Streaming. © 2010 Springer Science+Business Media, LLC.
KW - Automatic Parallelisation
KW - Compilers
KW - HiPEAC
KW - Parallel architectures
KW - Streaming applications
U2 - 10.1007/s10766-010-0132-7
DO - 10.1007/s10766-010-0132-7
M3 - Article
SN - 0885-7458
VL - 39
SP - 397
EP - 450
JO - International Journal of Parallel Programming
JF - International Journal of Parallel Programming
IS - 3
ER -