In this paper, we characterize and analyze an increasingly popular style of programming for the GPU called Persistent Threads (PT). We present a concise formal definition for this programming style, and discuss the difference between the traditional GPU programming style (nonPT) and PT, why PT is attractive for some high-performance usage scenarios, and when using PT may or may not be appropriate. We identify limitations of the nonPT style and identify four primary use cases it could be useful in addressing -- CPU-GPU synchronization, load balancing/irregular parallelism, producer-consumer locality, and global synchronization. Through micro-kernel benchmarks we show the PT approach can achieve up to an order-of-magnitude speedup over nonPT...
High compute-density with massive thread-level parallelism of Graphics Processing Units (GPUs) is be...
The Graphics Processing Unit (GPU) has become a mainstream computing platform for a wide range of ap...
GPUs have become popular due to their high computational power. Data scientists rely on GPUs to proc...
In this paper, we characterize and analyze an increasingly popular style of programming for the GPU ...
In this paper we present a heavily exploration oriented implementation of genetic algorithms to be e...
Programming models such as CUDA and OpenCL allow the programmer to specify the independence of threa...
Thread parallel hardware, as the Graphics Processing Units (GPUs), greatly outperform CPUs in provid...
Abstract—Heterogeneous architectures consisting of general-purpose CPUs and throughput-optimized GPU...
<p>Heterogeneous architectures consisting of general-purpose CPUs and throughput-optimized GPUs are ...
Many applications with regular parallelism have been shown to benefit from using Graphics Processing...
We propose a GPU fine-grained load-balancing abstraction that decouples load balancing from work pro...
The objective of this thesis is the development, implementation and optimization of a GPU execution ...
As modern GPU workloads become larger and more complex, there is an ever-increasing demand for GPU c...
2018-02-23Graphics Processing Units (GPUs) are designed primarily to execute multimedia, and game re...
Abstract-Graphic Processing Units (GPUs) achieve latency tolerance by exploiting massive amounts of ...
High compute-density with massive thread-level parallelism of Graphics Processing Units (GPUs) is be...
The Graphics Processing Unit (GPU) has become a mainstream computing platform for a wide range of ap...
GPUs have become popular due to their high computational power. Data scientists rely on GPUs to proc...
In this paper, we characterize and analyze an increasingly popular style of programming for the GPU ...
In this paper we present a heavily exploration oriented implementation of genetic algorithms to be e...
Programming models such as CUDA and OpenCL allow the programmer to specify the independence of threa...
Thread parallel hardware, as the Graphics Processing Units (GPUs), greatly outperform CPUs in provid...
Abstract—Heterogeneous architectures consisting of general-purpose CPUs and throughput-optimized GPU...
<p>Heterogeneous architectures consisting of general-purpose CPUs and throughput-optimized GPUs are ...
Many applications with regular parallelism have been shown to benefit from using Graphics Processing...
We propose a GPU fine-grained load-balancing abstraction that decouples load balancing from work pro...
The objective of this thesis is the development, implementation and optimization of a GPU execution ...
As modern GPU workloads become larger and more complex, there is an ever-increasing demand for GPU c...
2018-02-23Graphics Processing Units (GPUs) are designed primarily to execute multimedia, and game re...
Abstract-Graphic Processing Units (GPUs) achieve latency tolerance by exploiting massive amounts of ...
High compute-density with massive thread-level parallelism of Graphics Processing Units (GPUs) is be...
The Graphics Processing Unit (GPU) has become a mainstream computing platform for a wide range of ap...
GPUs have become popular due to their high computational power. Data scientists rely on GPUs to proc...