A framework for Compiler Level statistical analysis over customized VLIW architecture

Abstract

Very Long Instruction Word (VLIW) application specific processors represent an attractive solution for embedded computing, offering significant computational power with reduced hardware complexity. However, they impose higher compiler complexity since the instructions are executed in parallel based on the static compiler schedule. Therefore, finding a promising set of compiler transformations and defining their effects have a significant impact on the overall system performance. The proposed methodology provides the designer with an integrated framework to automatically (i) generate optimized application-specific VLIW architectural configurations and (ii) analyze compiler level transformations, enabling application-specific compiler tuning over customized VLIW system architectures. We based the aforementioned analysis on a Design of Experiments (DoEs) procedure that captures in a statistical manner the higher order effects among different sets of activated compiler transformations. Applying the proposed methodology onto real-case embedded application scenarios, we show that (i) only a limited set of compiler transformations exposes high confidence level (over 95%) in affecting the performance and (ii) using them we could be able to achieve gains between (16-23)% in comparison to the default optimization levels.

Publication
2013 IFIP/IEEE 21st International Conference on Very Large Scale Integration (VLSI-SoC)
Vittorio Zaccaria
Vittorio Zaccaria
Associate Professor

I am an associate professor at Politecnico di Milano and I have worked in embedded processor architecture R&D for one of the top semiconductor companies in the world. My group is currently working on topics related to embedded systems (hardware and software), security, cryptography, operating systems.

Gianluca Palermo
Gianluca Palermo
Full Professor

Gianluca Palermo received the M.Sc. degree in Electronic Engineering in 2002, and the Ph.D degree in Computer Engineering in 2006 from Politecnico di Milano. He is currently an associate professor at Department of Electronics and Information Technology in the same University. Previously he was also consultant engineer in the Low Power Design Group of AST – STMicroelectronics working on network on-chip and research assistant at the Advanced Learning and Research Institute (ALaRI) of the Università della Svizzera italiana (Switzerland). His research interests include design methodologies and architectures for embedded and HPC systems, focusing on AutoTuning aspects.