As technology scales, GPUs are forecasted to incorporate an ever-increasing amount of
computing resources to support thread-level parallelism. But even with the best effort …

This paper presents Warped-Compression, a warp-level register compression scheme for
reducing GPU power consumption. This work is motivated by the observation that the …

Graphics processing units (GPUs) are moving towards supporting concurrent kernel
execution where multiple kernels may be co-executed on the same GPU and even on the …

The current trend of ever-increasing performance in scientific applications comes with
tremendous growth in energy consumption. In this paper, we present GreenMM framework …

This paper presents a pre-execution approach for improving GPU performance, called P-
mode (pre-execution mode). GPUs utilize a number of concurrent threads for hiding …

Value locality, the recurrence of a previously-seen value, has been the enabler of myriad
optimization techniques in traditional processors. Value similarity relaxes the constraint of …

Graphics Processing Units (GPUs) are widely used as the accelerator of choice for
applications with massively data-parallel tasks. However, recent studies show that GPUs …

Graphics Processing Units (GPUs) are the accelerator of choice in a variety of application
domains, because they can accelerate massively parallel workloads and can be easily …

Graphics Processing Units (GPUs) use massive multi-threading coupled with static
scheduling to hide instruction latencies. Despite this, memory instructions pose a challenge …

Graphics Processing Units (GPUs) have been employed in embedded systems to handle
increased amounts of computation and to satisfy the timing requirement. Due to the small …