No abstract

Instruction caches have traditionally been used to improve software performance. Recently, several tiny instruction cache designs, including filter caches and dynamic loop caches, have been proposed to instead reduce software power. We propose several new tiny instruction cache designs, including preloaded loop caches, and one-level and two-level hybrid dynamic/preloaded loop caches. We evaluate the existing and proposed designs on embedded system software benchmarks from both the Powerstone and MediaBench suites, on two different processor architectures, for a variety of different technologies. We show on average that filter caching achieves the best instruction fetch energy reductions of 60-80%, but at the cost of about 20% performance degradation, which could also affect overall energy savings. We show that dynamic loop caching gives good instruction fetch energy savings of about 30%, but that if a designer is able to profile a program, preloaded loop caching can more than double the savings. We describe automated methods for quickly determining the best loop cache configuration, methods useful in a core-based design flow.

Recent years have seen the evolution of networks of tiny low power computing blocks, known as sensor networks. In one class of sensor networks, a non-expert user, who has little or no experience with electronics or programming, selects, connects and/or configures one or more blocks such that the blocks compute a particular Boolean logic function of sensor values. We describe a series of experiments showing that non-expert users have much difficulty with a block based on Boolean logic truth tables, and that a logic block having a sentence-like structure with some configurable switches yields a better success rate. We also show that a particular use of color with a truth table improves results over a traditional truth table.

No abstract

We describe our first efforts to develop a set of off-the-shelf hardware components that ordinary people could connect to build a simple but useful class of embedded systems.