On the Role of Deterministic Fine-Grain Data Synchronization for Scientific Applications: A Revisit in the Emerging Many-Core Era

The design of microprocessor chip for high-end computing systems is moving towards many-core architectures with 10s or 100+ processing units. An important class of the target applications for such architectures are scientific numerical computations, many of which are intrinsically deterministic - that is for a given input a fixed output (result) should be produced no matter how the program is parallelized. It is critical that the read-after-write data dependencies in such programs should be implemented correctly and efficiently via fine-grain data synchronization. In this paper, we investigate the parallelization of three representative scientific computation kernels using fine-grain data synchronization supported by an recently proposed architectural mechanism for many-core chips, called Synchronization State Buffer (SSB) [25]. Using detailed simulation on a simulator for the IBM 160-core Cyclops-64 chip architecture with the SSB extension, our experiments demonstrate significant performance advantage of using fine-grain data synchronization based parallelization schemes for scientific workloads.