Jiashen Cao's repositories
ann-benchmarks
Benchmarks of approximate nearest neighbor libraries in Python
evadb
Bring AI inside your database system
fast-interconnects-demo
How to use fast GPU interconnects in practice
gpgpu-sim_distribution
GPGPU-Sim provides a detailed simulation model of contemporary NVIDIA GPUs running CUDA and/or OpenCL workloads. It includes support for features such as TensorCores and CUDA Dynamic Parallelism as well as a performance visualization tool, AerialVisoin, and an integrated energy model, GPUWattch.
ICDE2019-GPU-Join
Implementation of the algorithm described in "Hardware-conscious Hash-Joins on GPUs" paper presented in ICDE 2019
jiashenC.github.io
Personal Website
PipeSwitch
PipeSwitch: Fast Pipelined Context Switching for Deep Learning Applications
pytorch
Tensors and Dynamic neural networks in Python with strong GPU acceleration
ScaledYOLOv4
Scaled-YOLOv4: Scaling Cross Stage Partial Network
smart-quantization
Smart Quantization for Deep Neural Networks (SmaQ)
TPC-H-Skew
TPC-H benchmark with skew factor enabled
tpch_dbgen_zipf_skew
TPC-H datagen with zipfian skew
Yet-Another-EfficientDet-Pytorch
The pytorch re-implement of the official efficientdet with SOTA performance in real time and pretrained weights.