213 citations · 934 across the 47 of their papers we have counts for
9 papers · 1 filter
Load-balanced Gather-scatter Patterns for Sparse Deep Neural Networks
Fei Sun, Minghai Qin, Tianyun Zhang +6
Deep neural networks (DNNs) have been proven to be effective in solving many real-life problems, but its high computation cost prohibits those models from being deployed to edge de…
Understanding GNN Computational Graph: A Coordinated Computation, IO, and Memory Perspective
Hengrui Zhang, Zhongming Yu, Guohao Dai +4
Graph Neural Networks (GNNs) have been widely used in various domains, and GNNs with sophisticated computational graph lead to higher latency and larger memory consumption. Optimiz…
Paulihedral: A Generalized Block-Wise Compiler Optimization Framework For Quantum Simulation Kernels
Gushu Li, Anbang Wu, Yunong Shi +3
The quantum simulation kernel is an important subroutine appearing as a very long gate sequence in many quantum programs. In this paper, we propose Paulihedral, a block-wise compil…
H2Learn: High-Efficiency Learning Accelerator for High-Accuracy Spiking Neural Networks
Ling Liang, Zheng Qu, Zhaodong Chen +6
Although spiking neural networks (SNNs) take benefits from the bio-plausible neural modeling, the low accuracy under the common local synaptic plasticity learning rules limits thei…
Efficient Sparse Matrix Kernels based on Adaptive Workload-Balancing and Parallel-Reduction
Guyue Huang, Guohao Dai, Yu Wang +2
Sparse matrix-vector and matrix-matrix multiplication (SpMV and SpMM) are fundamental in both conventional (graph analytics, scientific computing) and emerging (sparse DNN, GNN) do…
Effective Model Sparsification by Scheduled Grow-and-Prune Methods
Xiaolong Ma, Minghai Qin, Fei Sun +7
Deep neural networks (DNNs) are effective in solving many real-world problems. Larger DNN models usually exhibit better quality (e.g., accuracy) but their excessive computation res…
A Case for 3D Integrated System Design for Neuromorphic Computing & AI Applications
Eren Kurshan, Hai Li, Mingoo Seok +1
Over the last decade, artificial intelligence has found many applications areas in the society. As AI solutions have become more sophistication and the use cases grew, they highlig…
IronMan: GNN-assisted Design Space Exploration in High-Level Synthesis via Reinforcement Learning
Nan Wu, Yuan Xie, Cong Hao
Despite the great success of High-Level Synthesis (HLS) tools, we observe several unresolved challenges: 1) the high-level abstraction of programming styles in HLS sometimes concea…
A Survey of Machine Learning for Computer Architecture and Systems
Nan Wu, Yuan Xie
It has been a long time that computer architecture and systems are optimized for efficient execution of machine learning (ML) models. Now, it is time to reconsider the relationship…