Search Results for author:
Found 7 papers, 2 papers with code
NeuraChip: Accelerating GNN Computations with a Hash-based Decoupled Spatial Accelerator
We introduce a rolling eviction strategy to mitigate data idling in on-chip memory as well as address the prevalent issue of memory bloat in sparse graph computations.
MaxK-GNN: Extremely Fast GPU Kernel Design for Accelerating Graph Neural Networks Training
In this paper, we present MaxK-GNN, an advanced high-performance GPU training system integrating algorithm and system innovation.
SECDA: Efficient Hardware/Software Co-Design of FPGA-based DNN Accelerators for Edge Inference
In this paper we propose SECDA, a new hardware/software co-design methodology to reduce design time of optimized DNN inference accelerators on edge devices with FPGAs.
Achieving on-Mobile Real-Time Super-Resolution with Neural Architecture and Pruning Search
Though recent years have witnessed remarkable progress in single image super-resolution (SISR) tasks with the prosperous development of deep neural networks (DNNs), the deep learning methods are confronted with the computation and memory consumption issues in practice, especially for resource-limited platforms such as mobile devices.
A Smart Background Scheduler for Storage Systems
In today's enterprise storage systems, supported data services such as snapshot delete or drive rebuild can cause tremendous performance interference if executed inline along with heavy foreground IO, often leading to missing SLOs (Service Level Objectives).
Iterative Spectral Method for Alternative Clustering
Given a dataset and an existing clustering as input, alternative clustering aims to find an alternative partition.
Defensive Dropout for Hardening Deep Neural Networks under Adversarial Attacks
Based on the observations of the effect of test dropout rate on test accuracy and attack success rate, we propose a defensive dropout algorithm to determine an optimal test dropout rate given the neural network model and the attacker's strategy for generating adversarial examples. We also investigate the mechanism behind the outstanding defense effects achieved by the proposed defensive dropout.
