Sparse matrices are widely used in graph and data analytics, machine learning, engineering
and scientific applications. This paper describes and analyzes OuterSPACE, an accelerator …

Near-Data-Processing (NDP) architectures present a promising way to alleviate data
movement costs and can provide significant performance and energy benefits to parallel …

For parallelism to become tractable for mass programmers, shared-memory languages and
environments must evolve to enforce disciplined practices that ban" wild shared-memory …

Much of the complexity and overhead (directory, state bits, invalidations) of a typical
directory coherence implementation stems from the effort to make it" invisible" even to the …

Abstract System and methods for cache coherence in a multi-core processing environment
having a local/shared cache hierarchy. The system includes multiple processor cores, a …

Coherent shared virtual memory (cSVM) is highly coveted for heterogeneous architectures
as it will simplify programming across different cores and manycore accelerators. In this …

To achieve exascale computing, fundamental hardware architectures must change. This will
significantly impact scientific applications that run on current high performance computing …

Traditional directory coherence protocols are designed for the strictest consistency model,
sequential consistency (SC). When they are used for chip multiprocessors (CMPs) that …

A coherent global address space in a distributed system enables shared memory
programming in a much larger scale than a single multicore or a single SMP. Without …

Recent work has shown that disciplined shared-memory programming models that provide
deterministic-by-default semantics can simplify both parallel software and hardware …