A curated list of research in machine learning system. I also summarize some papers if I think they are really interesting.

Accelerating Deep Learning Training (DLT) from Storage Perspective

TidalDecode: A Fast and Accurate LLM Decoding with Position Persistent Sparse Attention

GPT-like Large Language Model Pretrained on Inspur's Yuan Dataset

Enhancing TVM Autotuner to Optimize for Energy Efficiency

My collection of Distributed system papers, especially for ML.

Code for "Apparate: Rethinking Early Exits to Tame Latency-Throughput Tensions in ML Serving" [SOSP '24]

Website for MLSys Group @ UCSD

GPU-initiated Large-scale GNN System

Federated Learning Systems Paper List

NAACL '24 (Best Demo Paper RunnerUp) / MlSys @ NeurIPS '23 - RedCoast: A Lightweight Tool to Automate Distributed Training and Inference

sensAI: ConvNets Decomposition via Class Parallelism for Fast Inference on Live Data

A ChatGPT(GPT-3.5) & GPT-4 Workload Trace to Optimize LLM Serving Systems

Optimal Sparse Decision Trees

Materials for my 2021 NYU class on NLP and ML Systems (Master of Engineering).

SVDQuant: Absorbing Outliers by Low-Rank Components for 4-Bit Diffusion Models

A scalable & efficient active learning/data selection system for everyone.

An acceleration library that supports arbitrary bit-width combinatorial quantization operations

Deep Learning Energy Measurement and Optimization

Machine Learning Framework for Operating Systems - Brings ML to Linux kernel