89 citations · 187 across the 12 of their papers we have counts for
4 papers · 1 filter
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…
Serpens: A High Bandwidth Memory Based Accelerator for General-Purpose Sparse Matrix-Vector Multiplication
Linghao Song, Yuze Chi, Licheng Guo +1
Sparse matrix-vector multiplication (SpMV) multiplies a sparse matrix with a dense vector. SpMV plays a crucial role in many applications, from graph analytics to deep learning. Th…
Pyxis: An Open-Source Performance Dataset of Sparse Accelerators
Linghao Song, Yuze Chi, Jason Cong
Specialized accelerators provide gains of performance and efficiency in specific domains of applications. Sparse data structures or/and representations exist in a wide range of app…
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…