Cloud Computing is an emerging computing paradigm. It shares massively scalable, elastic
resources (eg, data, calculations, and services) transparently among the users over a …

Processing data in or near memory (PIM), as opposed to in conventional computational units
in a processor, can greatly alleviate the performance and energy penalties of data transfers …

Graphics Processing Units (GPUs) have numerous configuration and design options,
including core frequency, number of parallel compute units (CUs), and available memory …

Emerging GPGPU architectures, along with programming models like CUDA and OpenCL,
offer a cost-effective platform for many applications by providing high thread level …

High performance in GPGPU workloads is obtained by maximizing parallelism and fully
utilizing the available resources. The thousands of threads are assigned to each core in …

In this paper, we present techniques that coordinate the thread scheduling and prefetching
decisions in a General Purpose Graphics Processing Unit (GPGPU) architecture to better …

This paper uses hardware thread scheduling to improve the performance and energy
efficiency of divergent applications on GPUs. We propose Divergence-Aware Warp …

The massive parallel architecture enables graphics processing units (GPUs) to boost
performance for a wide range of applications. Initially, GPUs only employ scratchpad …

Heterogeneous architectures consisting of general-purpose CPUs and throughput-
optimized GPUs are projected to be the dominant computing platforms for many classes of …

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 …