18 citations · 30 across the 4 of their papers we have counts for
4 papers
A Compilation Flow for the Generation of CNN Inference Accelerators on FPGAs
Seung-Hun Chung, Tarek S. Abdelrahman
We present a compilation flow for the generation of CNN inference accelerators on FPGAs. The flow translates a frozen model into OpenCL kernels with the TVM compiler and uses the I…
Pipelined Training with Stale Weights of Deep Convolutional Neural Networks
Lifu Zhang, Tarek S. Abdelrahman
The growth in the complexity of Convolutional Neural Networks (CNNs) is increasing interest in partitioning a network across multiple accelerators during training and pipelining th…
Fast On-the-fly Retraining-free Sparsification of Convolutional Neural Networks
Amir H. Ashouri, Tarek S. Abdelrahman, Alwyn Dos Remedios
Modern Convolutional Neural Networks (CNNs) are complex, encompassing millions of parameters. Their deployment exerts computational, storage and energy demands, particularly on emb…
Automatic Tuning of Local Memory Use on GPGPUs
Tianyi David Han, Tarek S. Abdelrahman
The use of local memory is important to improve the performance of OpenCL programs. However, its use may not always benefit performance, depending on various application characteri…