Optimizing multicore performance with message driven execution: A case study

Abstract

With the growing amount of parallelism available on today's multicore processors, achieving good performance at scale is challenging. We approach this issue through an alternative to traditional thread-based paradigms for writing shared memory programs, namely message driven multicore programming. We study a number of optimizations that improve the efficiency of message driven programs on multicore architectures. In particular, we focus on the following runtime system-enabled optimizations: (i) grainsize control to effect a good concurrency-overhead tradeoff, (ii) dynamic balancing of processor load, (iii) low-overhead, asynchronous communication for lock-free and message-driven execution and (iv) communication-reduction through a novel chunked shared array abstraction. The practical impact of these optimizations is quantified through a parallel kd-tree construction program written in the message-driven paradigm. A comparison of the optimized code with a state-of-the-art parallel kd-tree construction program is also presented.