Jason Cong

Latest

• CHARM 2.0: Composing Heterogeneous Accelerators for Deep Learning on Versal ACAP Architecture (🔥📣New Paper & Project🔥📣! )
• CHARM: Composing Heterogeneous AcceleRators for Matrix Multiply on Versal ACAP Architecture (🔥📣New Paper & Project🔥📣! )
• MOCHA: Multinode Cost Optimization in Heterogeneous Clouds with Accelerators
• Algorithm-Hardware Co-design for BQSR Acceleration in Genome Analysis ToolKit
• Customizable Domain Specific Computing
• Caffeine: Towards Uniformed Representation and Acceleration for Deep Convolutional Neural Networks (🔥Best Paper)
• SODA: Stencil with Optimized Dataflow Architecture (🔥Best Paper Nominee)
• Best-effort FPGA programming: a few steps can go a long way
• Doppio: I/O-Aware Performance Analysis, Modeling and Optimization for In-Memory Computing Framework(🔥Best Paper Nominee)
• Latte: Locality Aware Transformation for High-Level Synthesis
• ST-Accel: A High-Level Programming Platform for Streaming Applications on FPGA
• Bandwidth Optimization Through On-Chip Memory Restructuring for HLS
• Caffeine: Towards Uniformed Representation and Acceleration for Deep Convolutional Neural Networks
• Energy Efficiency of Full Pipelining: A Case Study for Matrix Multiplication
• ARAPrototyper: Enabling Rapid Prototyping and Evaluation for Accelerator-Rich Architecture
• CS-BWAMEM: A fast and scalable read aligner at the cloud scale for whole genome sequencing
• A Fully Pipelined and Dynamically Composable Architecture of CGRA