An efficient method for system-level exploration of global optimum in a parameterized ASIP design
This paper proposes an efficient method for design space exploration of the global optimum configuration for parameterized ASIPs. The method not only guarantees the optimum configuration, but also provides robust speedup for a wide range of processor architectures such as SoC, ASIC as well as ASIP. The optimization procedure within this method takes a two-steps approach. Firstly, design parameters are partitioned into clusters of inter-dependent parameters using parameter dependency information. Secondly, parameters are optimized for each cluster, the results of which are merged for global optimum. In such optimization, inferior configurations are extensively pruned with a detailed optimality mapping between dependent parameters. Experimental results with mediabench applications show an optimization speedup of 4.1 times faster than the previous work on average, which is significant improvement for practical use.
parameterized asip design space exploration global optimization