The continued growth in the processing power of FPGAs coupled with high
...
In this paper, we propose TAPA, an end-to-end framework that compiles a ...
Sparse matrix-vector multiplication (SpMV) multiplies a sparse matrix wi...
Specialized accelerators provide gains of performance and efficiency in
...
Sparse-Matrix Dense-Matrix multiplication (SpMM) is the key operator for...
We propose ReFloat, a principled approach for low-cost floating-point
pr...
Training Convolutional Neural Networks (CNNs) usually requires a large n...
We present a deep learning approach for vertex reconstruction of
neutrin...
With the rise of artificial intelligence in recent years, Deep Neural
Ne...
Object detectors have witnessed great progress in recent years and have ...
Object detectors have witnessed great progress in recent years and have ...
This paper presents GRAPHR, the first ReRAM-based graph processing
accel...
Brain inspired neuromorphic computing has demonstrated remarkable advant...