Finding near‐perfect parameters for hardware and code optimizations with automatic multi‐objective design space explorations

Abstract

SummaryIn the design process of computer systems or processor architectures, typically many different parameters are exposed to configure, tune, and optimize every component of a system. For evaluations and before production, it is desirable to know the best setting for all parameters. Processing speed is no longer the only objective that needs to be optimized; power consumption, area, and so on have become very important. Thus, the best configurations have to be found in respect to multiple objectives. In this article, we use a multi‐objective design space exploration tool called Framework for Automatic Design Space Exploration (FADSE) to automatically find near‐optimal configurations in the vast design space of a processor architecture together with a tool for code optimizations and hence evaluate both automatically. As example, we use the Grid ALU Processor (GAP) and its postlink optimizer called GAPtimize, which can apply feedback‐directed and platform‐specific code optimizations. Our results show that FADSE is able to cope with both design spaces. Less than 25% of the maximal reasonable hardware effort for the scalable elements of the GAP is enough to achieve the processor's performance maximum. With a performance reduction tolerance of 10%, the necessary hardware complexity can be further reduced by about two‐thirds. The found high‐quality configurations are analyzed, exhibiting strong relationships between the parameters of the GAP, the distribution of complexity, and the total performance. These performance numbers can be improved by applying code optimizations concurrently to optimizing the hardware parameters. FADSE can find near‐optimal configurations by effectively combining and selecting parameters for hardware and code optimizations in a short time. The maximum observed speedup is 15%. With the use of code optimizations, the maximum possible reduction of the hardware resources, while sustaining the same performance level, is 50%.Copyright © 2012 John Wiley & Sons, Ltd.

Recent developments in high‐performance computing and simulation: distributed systems, architectures, algorithms, and applications

“…‘Finding Near‐Perfect Parameters for Hardware and Code Optimizations by Automatic Multi‐Objective Design Space Explorations’ by Ralf Jahr, Horia Calborean, Lucian Vintan, and Theo Ungerer introduces FADSE, a design space exploration tool that automatically finds nearly optimal processor design configurations for a given code. Taking into account that performance is no longer the only objective subject to optimization (others comprise power consumption, area, etc.…”

Multi-objective hardware-software co-optimization for the SNIPER multi-core simulator

“…This domain-knowledge was integrated in the mutation genetic operator, with benefits in reducing the search time and improving the solutions' quality, as presented in [1] and [2]. For the further reducing of the search time, distributed evaluations of the individuals are allowed; a database saves the simulation results for future reuse, while checkpointing and error recovery mechanisms oversee the simulations, so that the DSE process is not started again from scratch.…”

“…D. student Horia Calborean under the supervision of Prof. Lucian Vintan at the "Lucian Blaga" University of Sibiu. Computation-intensive searches using state of the art evolutionary multi-objective algorithms, guided by the human experience are automatically performed by FADSE as presented in our previous works [1], [2].…”

River

“…The Netchip compiler in Bertozzi et al [2005] explores and generates applicationspecific communication architectures, whereas the authors of Jahr et al [2012] focus on processor architectures at design time and Marianik et al [2012] on runtime reconfigurable processors. Depending on how our architectural approach and presynthesized repository are integrated into other projects, it would be possible to combine one or more of these methods and tools for design space exploration with our contributions.…”