In the past decade, Graphics Processing Units have played an important role in the field of
high-performance computing and they still advance new fields such as IoT, autonomous …

This work observes that a large fraction of the computations performed by Deep Neural
Networks (DNNs) are intrinsically ineffectual as they involve a multiplication where one of …

General-purpose GPUs (GPGPUs) are becoming prevalent in mainstream computing, and
performance per watt has emerged as a more crucial evaluation metric than peak …

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

GPUs have been used to accelerate many regular applications and, more recently, irregular
applications in which the control flow and memory access patterns are data-dependent and …

Due to their massive computational power, graphics processing units (GPUs) have become
a popular platform for executing general purpose parallel applications. GPU programming …

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 …

The Single Instruction Multiple Data (SIMD) architecture, supported by various high-
performance computing platforms, efficiently utilizes data-level parallelism. The SIMD model …

The proliferation of heterogeneous compute platforms, of which CPU/GPU is a prevalent
example, necessitates a manageable programming model to ensure widespread adoption …