Optimal speedup on a low-degree multi-core parallel architecture (LoPRAM)

Over the last five years, major microprocessor manufacturers have released plans for a rapidly increasing number of cores per microprossesor, with upwards of 64 cores by 2015. In this setting, a sequential RAM computer will no longer accurately reflect the architecture on which algorithms are being executed. In this paper we propose a model of low degree parallelism (LoPRAM) which builds upon the RAM and PRAM models yet better reflects recent advances in parallel (multi-core) architectures. This model supports a high level of abstraction that simplifies the design and analysis of parallel programs. More importantly we show that in many instances it naturally leads to work-optimal parallel algorithms via simple modifications to sequential algorithms.