Pinned Repositories
GraphMini
Source code for GraphMini and the two baseline systems (GraphPi and Dryadic) for comparison.
497s-team-e
GitHub repository for Team E's Scalable Web Systems Project
cnpy
library to read/write .npy and .npz files in C/C++
cs326-final-lambda
A forum for UMass student to share their off-campus living experiences
cuvs
cuVS - a library for vector search and clustering on the GPU
dgl
Python package built to ease deep learning on graph, on top of existing DL frameworks.
GraphMini
GraphMini is a high-performance graph pattern-matching system.
GraphPi
MaximalClique
A faster algorithm for finding maximal cliques.
P3-GNN
Implementation for "P3: Distributed Deep Graph Learning at Scale"
Juelin-Liu's Repositories
Juelin-Liu/MaximalClique
A faster algorithm for finding maximal cliques.
Juelin-Liu/P3-GNN
Implementation for "P3: Distributed Deep Graph Learning at Scale"
Juelin-Liu/497s-team-e
GitHub repository for Team E's Scalable Web Systems Project
Juelin-Liu/cnpy
library to read/write .npy and .npz files in C/C++
Juelin-Liu/cs326-final-lambda
A forum for UMass student to share their off-campus living experiences
Juelin-Liu/cuvs
cuVS - a library for vector search and clustering on the GPU
Juelin-Liu/dgl
Python package built to ease deep learning on graph, on top of existing DL frameworks.
Juelin-Liu/GraphMini
GraphMini is a high-performance graph pattern-matching system.
Juelin-Liu/GraphPi
Juelin-Liu/hnswlib
Header-only C++/python library for fast approximate nearest neighbors
Juelin-Liu/Juelin-Liu.github.io
Juelin-Liu/METIS
METIS - Serial Graph Partitioning and Fill-reducing Matrix Ordering
Juelin-Liu/oneTBB
oneAPI Threading Building Blocks (oneTBB)
Juelin-Liu/torch-quiver
PyTorch Library for Low-Latency, High-Throughput Graph Learning on GPUs.
Juelin-Liu/npmetis
Juelin-Liu/ParMETIS
ParMETIS - Parallel Graph Partitioning and Fill-reducing Matrix Ordering
Juelin-Liu/pebble
Juelin-Liu/puck
Puck is a high-performance ANN search engine
Juelin-Liu/raft
RAFT contains fundamental widely-used algorithms and primitives for machine learning and information retrieval. The algorithms are CUDA-accelerated and form building blocks for more easily writing high performance applications.
Juelin-Liu/ray
Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
Juelin-Liu/rnn-descent