Novel accelerated methods for convolution neural network with matrix core
Y Guo, L Lu, S Zhu - The Journal of Supercomputing, 2023 - Springer
The powerful parallel computing capability of GPU and the development of matrix
processing unit in recent years provide more possibilities to improve the performance of …
processing unit in recent years provide more possibilities to improve the performance of …
WASP: Exploiting GPU Pipeline Parallelism with Hardware-Accelerated Automatic Warp Specialization
Graphics processing units (GPUs) are an important class of parallel processors that offer
high compute throughput and memory bandwidth. GPUs are used in a variety of important …
high compute throughput and memory bandwidth. GPUs are used in a variety of important …
A Decomposable Winograd Method for N–D Convolution Acceleration in Video Analysis
Winograd's minimal filtering algorithm has been widely used in 2-D Convolutional Neural
Networks (CNNs) to reduce the number of multiplications for faster processing. However, it is …
Networks (CNNs) to reduce the number of multiplications for faster processing. However, it is …