A binary instrumentation tool for the Blackfin processor

  • Authors:
  • Enqiang Sun;David Kaeli

  • Affiliations:
  • Northeastern University, Boston, MA;Northeastern University, Boston, MA

  • Venue:
  • Proceedings of the Workshop on Binary Instrumentation and Applications
  • Year:
  • 2009

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Abstract

While a large number of program profiling and instrumentation tools have been developed to support hardware and software analysis on general purpose systems, there is a general lack of sophisticated tools available for embedded architectures. Embedded systems are sensitive to performance bottlenecks, memory leaks, and software inefficiencies. There is a growing need to develop more sophisticated profiling and instrumentation tools in this rapidly growing design space. In this paper we describe, DSPInst, a binary instrumentation tool for the Analog Device's Blackfin family of Digital Signal Processors (DSPs). DSPInst provides for fine-grained control over the execution of programs. Instrumentation tool users are able to gain transparent access to the processor and memory state at instruction boundaries, without perturbing the architected program state. DSPInst provides a platform for building a wide range of customized analysis tools at an instruction level granularity. To demonstrate the utility of this toolset, we provide an example analysis and optimization tool that performs dynamic voltage and frequency scaling to balance performance and power.