5 citations · 13 across the 6 of their papers we have counts for
3 papers · 1 filter
Enabling Automated FPGA Accelerator Optimization Using Graph Neural Networks
Atefeh Sohrabizadeh, Yunsheng Bai, Yizhou Sun +1
High-level synthesis (HLS) has freed the computer architects from developing their designs in a very low-level language and needing to exactly specify how the data should be transf…
SPA-GCN: Efficient and Flexible GCN Accelerator with an Application for Graph Similarity Computation
Atefeh Sohrabizadeh, Yuze Chi, Jason Cong
While there have been many studies on hardware acceleration for deep learning on images, there has been a rather limited focus on accelerating deep learning applications involving…
Sextans: A Streaming Accelerator for General-Purpose Sparse-Matrix Dense-Matrix Multiplication
Linghao Song, Yuze Chi, Atefeh Sohrabizadeh +3
Sparse-Matrix Dense-Matrix multiplication (SpMM) is the key operator for a wide range of applications, including scientific computing, graph processing, and deep learning. Architec…