Impact of JVM superoperators on energy consumption in resource-constrained embedded systems

ABSTRACT

Energy consumption is one of the most important issues in resource-constrained embedded systems. Many such systems run Java-based applications due to Java's architecture-independent format (bytecode). Standard techniques for executing bytecode programs, e.g. interpretation or just-in-time compilation, have performance or memory issues that make them unsuitable for resource-constrained embedded systems.

A superoperator-extended, lightweight Java Virtual Machine (JVM) can be used in resource-constrained embedded systems to improve performance and reduce memory consumption. This paper shows that such a JVM also significantly reduces energy consumption. This is due primarily to a considerable reduction in the number of memory accesses and thus in energy consumption in the instruction and data TLBs and caches and, in most cases, in DRAM energy consumption. Since the fraction of processor energy dissipated in these units is approximately 60%, the energy savings achieved are significant.

The paper evaluates the number of load, store, and computational instructions eliminated by the use of proposed superoperators as compared to a simple interpreter on a set of embedded benchmarks. Using cache and DRAM per access energy we estimate the total processor/DRAM energy saved by using our JVM. Our results show that with 32KB caches the reduction in energy consumption ranges from 40% to 60% of the overall processor, plus DRAM energy. Even higher savings may be achieved with smaller caches and increased access to DRAM as DRAM access energy is fairly high.

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INDEX TERMS

Primary Classification:
  C. Computer Systems Organization
  C.4 PERFORMANCE OF SYSTEMS
      Subjects: Measurement techniques

Additional Classification:
  C. Computer Systems Organization
  C.4 PERFORMANCE OF SYSTEMS
      Subjects: Modeling techniques

  D. Software
  D.3 PROGRAMMING LANGUAGES
      D.3.4 Processors
          Subjects: Optimization

General Terms:
Experimentation, Measurement, Performance

Keywords:
embedded systems, energy estimation, java virtual machine, profile-guided optimization, superoperators