Handling Parallelism in a Concurrency Model

Programming models for concurrency are optimized for dealing with nondeterminism, for example to handle asynchronously arriving events. To shield the developer from data race errors effectively, such models may prevent shared access to data altogether. However, this restriction also makes them unsuitable for applications that require data parallelism. We present a library-based approach for permitting parallel access to arrays while preserving the safety guarantees of the original model. When applied to SCOOP, an object-oriented concurrency model, the approach exhibits a negligible performance overhead compared to ordinary threaded implementations of two parallel benchmark programs.Comment: MUSEPAT 201

Design of High performance and Low power Simultaneous Multi-Threaded Processor

In this paper, we present the design of a High Performance Multi-Threaded Processor. Processing of high quality images is inevitable in applications such as, HD TV, Gaming Multimedia, etc. which require a great processing power with low power consumption. This can be achived with multi-threaded processors which optimally utilises the Functional Units (Fus). The speed of processing is as good as multi-core processors with lesser area. A conflict resolver (CR) is designed for scheduling the instructions, which involves allocation of Fu. The data move instructions are in majority in any of the programs; the corresponding logic blocks are replicated and speed of execution is further improved. We illustrated for two-threaded processorHowever, it is possible to extend the design for any number of threads by suitably redesigning the CR, and also replicate Transfer Logic and CPU Registers.DOI:http://dx.doi.org/10.11591/ijece.v3i3.253