Recent years have witnessed phenomenal growth in the computational capabilities and
applications of GPUs. However, this trend has also led to a dramatic increase in their power …

Due to the increasing demand of cloud resources, the ever-increasing number and scale of
cloud data centers make their massive power consumption a prominent issue today …

This article discusses the capabilities of state-of-the art GPU-based high-throughput
computing systems and considers the challenges to scaling single-chip parallel-computing …

This paper studies the effects of hardware thread scheduling on cache management in
GPUs. We propose Cache-Conscious Wave front Scheduling (CCWS), an adaptive …

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

General-purpose graphics processing units (GPG-PUs) are at their best in accelerating
computation by exploiting abundant thread-level parallelism (TLP) offered by many classes …

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 …

Massively parallel, throughput-oriented systems such as graphics processing units (GPUs)
offer high performance for a broad range of programs. They are, however, complex to …

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