A new generation of mobile applications requires reduced energy consumption without sacrificin execution performance. In this paper, we propose to respond to these conflictin demands with an innovative statically pipelined processor supported by an optimizing compiler. The central idea of the approach is that the control during each cycle for each portion of the processor is explicitly represented in each instruction. Thus the pipelining is in effect statically determined by the compiler. The benefit of this approach include simpler hardware and that it allows the compiler to perform optimizations that are not possible on traditional architectures. The initial results indicate that static pipelining can significantl reduce power consumption without adversely affecting performance.
Abstract-A new generation of mobile applications requires reduced energy consumption without sacrificing execution performance. In this paper, we propose to respond to these conflicting demands with an innovative statically pipelined processor supported by an optimizing compiler. The central idea of the approach is that the control during each cycle for each portion of the processor is explicitly represented in each instruction. Thus the pipelining is in effect statically determined by the compiler. The benefits of this approach include simpler hardware and that it allows the compiler to perform optimizations that are not possible on traditional architectures. The initial results indicate that static pipelining can significantly reduce power consumption without adversely affecting performance.
Despite the fact that we are firmly in the multicore era, the use of parallel programming is not as widespread as it could be -in the software industry or in education. There have been many calls to incorporate more parallel programming content into undergraduate computer science education. One obstacle to doing this is that the programming languages most commonly used for parallel programming are detailed, low-level languages such as C, C++, Fortran (with OpenMP or MPI), OpenCL and CUDA. These languages allow programmers to write very efficient code, but that is not so important for those whose goal is to learn the concepts of parallel computing. This paper introduces a parallel programming language called Tetra which provides parallel programming features as first class language features, and also provides garbage collection and is designed to be as simple as possible. Tetra also includes an integrated development environment which is specifically geared for debugging parallel programs and visualizing program execution across multiple threads.
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