Cache is designed to exploit locality; however, the role of on-chip L1 data caches on modern
GPUs is often awkward. The locality among global memory requests from different SMs …

General-purpose GPUs have been widely utilized to accelerate parallel applications. Given
a relatively complex programming model and fast architecture evolution, producing efficient …

The rise of general-purpose computing on GPUs has influenced architectural innovation on
them. The introduction of an on-chip cache hierarchy is one such innovation. High L1 miss …

Graph representations of data are ubiquitous in analytic applications. However, graph
workloads are notorious for having irregular memory access patterns with variable access …

Graphics processing units (GPUs) include a large amount of hardware resources for parallel
thread executions. However, the resources are not fully utilized during runtime, and …

Despite their ubiquity in many important big-data applications, graph analytic kernels
continue to challenge modern memory hierarchies due to their frequent, long-latency …

Modern GPUs suffer from cache contention due to the limited cache size that is shared
across tens of concurrently running warps. To increase the per-warp cache size prior …

A large fraction of the microprocessor energy is consumed by the data movement in the
system. One of the reasons is the inefficiency in the conventional cache design. Cache …

Modern processors have a large processor-memory frequency gap, which urges the
computer designer to address the issue of the inefficiency of the memory system …

There are two inherent obstacles to effectively using Graphics Processing Units (GPUs) for
query processing in search engines:(a) the highly restricted GPU memory space, and (b) the …