Java has been widely adopted as one of the software platforms for the seamless integration of diverse computing devices. Over the last year, there has been great momentum in adopting Java technology in devices such as cellphones, PDAs, and pagers where optimizing energy consumption is critical. Since, traditionally, the Java virtual machine (JVM), the cornerstone of Java technology, is tuned for performance, taking into account energy consumption requires reevaluation, and possibly redesign of the virtual machine. This motivates us to tune specific components of the virtual machine for a battery-operated architecture. As embedded JVMs are designed to run for long periods of time on limited-memory embedded systems, creating and managing Java objects is of critical importance. The garbage collector (GC) is an important part of the JVM responsible for the automatic reclamation of unused memory. This article shows that the GC is not only important for limited-memory systems but also for energy-constrained architectures. This article focuses on tuning the GC to reduce energy consumption in a multibanked memory architecture. Tuning the GC is important not because it consumes a sizeable portion of overall energy during execution, but because it influences the energy consumed in the memory during application execution. In particular, we present a GC-controlled leakage energy optimization technique that shuts off memory banks that do not hold live data. Using two different commercial GCs and a suite of thirteen mobile applications, we evaluate the effectiveness of the GC-controlled energy optimization technique and study its sensitivity to different parameters such as bank size, the garbage collection frequency, object allocation style, compaction style, and compaction frequency. We observe that the energy consumption of an embedded Java application can be significantly more if the GC parameters are not tuned appropriately. Further, we notice that the object allocation pattern and the number of memory banks available in the underlying architecture are limiting factors on how effectively GC parameters can be used to optimize the memory energy consumption.
All Science Journal Classification (ASJC) codes
- Hardware and Architecture