The use of application-specific accelerators to improve systems’ energy-efficiency and performance is becoming more prevalent. To overcome the tight area budget on embedded systems we propose an early detection tool that complements existing High-level Synthesis tools by identifying computationally similar synthesizable kernels that are used to build Shared Accelerators (SAs). SAs are specialized hardware accelerators that execute very different software kernels but share the common hardware functions between them. SAs can provide increased coverage if similarities between the dataflow and control flow of seemingly very different workloads are detected. Existing methods use either dynamic traces or analyze register transfer level (RTL) implementations to find these similarities which requires deep knowledge of RTL and the time-consuming RTL design process.

The resource requirements of application-specific accelerators challenge embedded system designers who have a tight area budget but must cover a range of possible software kernels. We propose an early detection methodology (ReconfAST) to identify computationally similar synthesizable kernels to build Shared Accelerators (SAs). SAs are specialized hardware accelerators that execute very different software kernels but share the common hardware functions between them. SAs increase the fraction of workloads covered by specialized hardware by detecting similarities in dataflow and control flow between seemingly very different workloads. Existing methods use either dynamic traces or analyze register transfer level (RTL) implementations to find these similarities which require deep knowledge of RTL and time-consuming design process.

Designers are turning toward hardware specialization through the use of application-specific accelerators to provide energy-efficiency and performance. We propose an early detection methodology to identify computationally similar and synthesize-able kernels that are used to build Shared Accelerators (SAs). SAs are specialized hardware accelerators that execute very different software kernels but share the common hardware functions between them. SAs can provide increased coverage if both data flow and control flow similarities between - seemingly very different- workloads are detected.