A Case for Hybrid Discrete-Continuous Architectures PROJECT TITLE :A Case for Hybrid Discrete-Continuous ArchitecturesABSTRACT:Current technology trends indicate that power- and energyefficiency can limit chip throughput in the longer term. Current solutions to these issues, either within the manner of programmable or fixed-function digital accelerators can soon reach their limits as microarchitectural overheads are successively trimmed. A important departure from current computing strategies is required to carry forward computing advances beyond digital accelerators. In this paper we have a tendency to describe how the energy-efficiency of a big class of issues can be improved by employing a hybrid of the discrete and continuous models of computation instead of the ever-present, ancient discrete model of computation. We have a tendency to present preliminary analysis of domains and benchmarks which will be accelerated with the new model. Analysis shows that Machine Learning, physics and up to 1-third of SPEC, RMS and Berkeley suite of applications will be accelerated with the new hybrid model. Did you like this research project? To get this research project Guidelines, Training and Code... Click Here facebook twitter google+ linkedin stumble pinterest An Overview of Static Pipelining Cache Impacts of Datatype Acceleration
