Selective Flexibility: Creating Domain-Specific Reconfigurable Arrays

摘要

Historically, hardware acceleration technologies have either been application-specific, therefore lacking in flexibility, or fully programmable, thereby suffering from notable inefficiencies on an application-by-application basis. To address the growing need for domain-specific acceleration technologies, this paper describes a design methodology (i) to automatically generate a domain-specific coarse-grained array from a set of representative applications and (ii) to introduce limited forms of architectural generality to increase the likelihood that additional applications can be successfully mapped onto it. In particular, coarse-grained arrays generated using our approach are intended to be integrated into customizable processors that use application-specific instruction set extensions to accelerate performance and reduce energy; rather than implementing these extensions using application-specific integrated circuit (ASIC) logic, which lacks flexibility, they can be synthesized onto our reconfigurable array instead, allowing the processor to be used for a variety of applications in related domains. Results show that our array is around $2times$ slower and $15times$ larger than an ultimately efficient ASIC implementation, and thus far more efficient than field-programmable gate arrays (FPGAs), which are known to be 3–4$times$ slower and 20–40$times$ larger. Additionally, we estimate that our array is usually around $2times$ larger and $2times$ slower than an accelerator synthesized using traditional datapath merging, which has, if any, very limited flexib- lity beyond the design set of DFGs.