Over the last five years, major microprocessor manufacturers have
released plans for a rapidly increasing number of cores per microprocessor, 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 work 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.
This is joint work with Alex Lopez-Ortiz and Reza Dorrigiv.