Optimizing multicore performance with message driven execution: A case study

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.