83 citations · 734 across the 57 of their papers we have counts for
18 papers · 1 filter
Tensor Recovery from Noisy and Multi-Level Quantized Measurements
Ren Wang, Meng Wang, Jinjun Xiong
Higher-order tensors can represent scores in a rating system, frames in a video, and images of the same subject. In practice, the measurements are often highly quantized due to the…
Helios: Heterogeneity-Aware Federated Learning with Dynamically Balanced Collaboration
Zirui Xu, Fuxun Yu, Jinjun Xiong +1
In this paper, we propose Helios, a heterogeneity-aware FL framework to tackle the straggler issue. Helios identifies individual devices' heterogeneous training capability, and the…
The Design and Implementation of a Scalable DL Benchmarking Platform
Cheng Li, Abdul Dakkak, Jinjun Xiong +1
The current Deep Learning (DL) landscape is fast-paced and is rife with non-uniform models, hardware/software (HW/SW) stacks, but lacks a DL benchmarking platform to facilitate eva…
DLBricks: Composable Benchmark Generation to Reduce Deep Learning Benchmarking Effort on CPUs (Extended)
Cheng Li, Abdul Dakkak, Jinjun Xiong +1
The past few years have seen a surge of applying Deep Learning (DL) models for a wide array of tasks such as image classification, object detection, machine translation, etc. While…
Benanza: Automatic Benchmark Generation to Compute "Lower-bound" Latency and Inform Optimizations of Deep Learning Models on GPUs
Cheng Li, Abdul Dakkak, Jinjun Xiong +1
As Deep Learning (DL) models have been increasingly used in latency-sensitive applications, there has been a growing interest in improving their response time. An important venue f…
MSU-Net: Multiscale Statistical U-Net for Real-time 3D Cardiac MRI Video Segmentation
Tianchen Wang, Jinjun Xiong, Xiaowei Xu +5
Cardiac magnetic resonance imaging (MRI) is an essential tool for MRI-guided surgery and real-time intervention. The MRI videos are expected to be segmented on-the-fly in real prac…
SkyNet: a Hardware-Efficient Method for Object Detection and Tracking on Embedded Systems
Xiaofan Zhang, Haoming Lu, Cong Hao +9
Object detection and tracking are challenging tasks for resource-constrained embedded systems. While these tasks are among the most compute-intensive tasks from the artificial inte…
SPGNet: Semantic Prediction Guidance for Scene Parsing
Bowen Cheng, Liang-Chieh Chen, Yunchao Wei +6
Multi-scale context module and single-stage encoder-decoder structure are commonly employed for semantic segmentation. The multi-scale context module refers to the operations to ag…
Analysis and Optimization of I/O Cache Coherency Strategies for SoC-FPGA Device
Seung Won Min, Sitao Huang, Mohamed El-Hadedy +3
Unlike traditional PCIe-based FPGA accelerators, heterogeneous SoC-FPGA devices provide tighter integrations between software running on CPUs and hardware accelerators. Modern hete…
XSP: Across-Stack Profiling and Analysis of Machine Learning Models on GPUs
Cheng Li, Abdul Dakkak, Jinjun Xiong +3
There has been a rapid proliferation of machine learning/deep learning (ML) models and wide adoption of them in many application domains. This has made profiling and characterizati…
SkyNet: A Champion Model for DAC-SDC on Low Power Object Detection
Xiaofan Zhang, Cong Hao, Haoming Lu +9
Developing artificial intelligence (AI) at the edge is always challenging, since edge devices have limited computation capability and memory resources but need to meet demanding re…
A Retrospective Recount of Computer Architecture Research with a Data-Driven Study of Over Four Decades of ISCA Publications
Omer Anjum, Wen-Mei Hwu, Jinjun Xiong
This study began with a research project, called DISCvR, conducted at the IBM-ILLINOIS Center for Cognitive Computing Systems Reseach. The goal of DISCvR was to build a practical N…
FPGA/DNN Co-Design: An Efficient Design Methodology for IoT Intelligence on the Edge
Cong Hao, Xiaofan Zhang, Yuhong Li +5
While embedded FPGAs are attractive platforms for DNN acceleration on edge-devices due to their low latency and high energy efficiency, the scarcity of resources of edge-scale FPGA…
Reinforcement Learning Based Text Style Transfer without Parallel Training Corpus
Hongyu Gong, Suma Bhat, Lingfei Wu +2
Text style transfer rephrases a text from a source style (e.g., informal) to a target style (e.g., formal) while keeping its original meaning. Despite the success existing works ha…
Document Similarity for Texts of Varying Lengths via Hidden Topics
Hongyu Gong, Tarek Sakakini, Suma Bhat +1
Measuring similarity between texts is an important task for several applications. Available approaches to measure document similarity are inadequate for document pairs that have no…
SCNN: A General Distribution based Statistical Convolutional Neural Network with Application to Video Object Detection
Tianchen Wang, Jinjun Xiong, Xiaowei Xu +1
Various convolutional neural networks (CNNs) were developed recently that achieved accuracy comparable with that of human beings in computer vision tasks such as image recognition,…
Revisiting the Evaluation of Uncertainty Estimation and Its Application to Explore Model Complexity-Uncertainty Trade-Off
Yukun Ding, Jinglan Liu, Jinjun Xiong +1
Accurately estimating uncertainties in neural network predictions is of great importance in building trusted DNNs-based models, and there is an increasing interest in providing acc…
Deep Learning for Multi-Messenger Astrophysics: A Gateway for Discovery in the Big Data Era
Gabrielle Allen, Igor Andreoni, Etienne Bachelet +45
This report provides an overview of recent work that harnesses the Big Data Revolution and Large Scale Computing to address grand computational challenges in Multi-Messenger Astrop…