299 citations · 810 across the 25 of their papers we have counts for
7 papers · 1 filter
Shift Parallelism: Low-Latency, High-Throughput LLM Inference for Dynamic Workloads
Mert Hidayetoglu, Aurick Qiao, Michael Wyatt +3
Efficient parallelism is necessary for achieving low-latency, high-throughput inference with large language models (LLMs). Tensor parallelism (TP) is the state-of-the-art method fo…
Arctic Inference with Shift Parallelism: Fast and Efficient Open Source Inference System for Enterprise AI
Samyam Rajbhandari, Mert Hidayetoglu, Aurick Qiao +5
Inference is now the dominant AI workload, yet existing systems force trade-offs between latency, throughput, and cost. Arctic Inference, an open-source vLLM plugin from Snowflake…
FastPersist: Accelerating Model Checkpointing in Deep Learning
Guanhua Wang, Olatunji Ruwase, Bing Xie +1
Model checkpoints are critical Deep Learning (DL) artifacts that enable fault tolerance for training and downstream applications, such as inference. However, writing checkpoints to…
ZeRO++: Extremely Efficient Collective Communication for Giant Model Training
Guanhua Wang, Heyang Qin, Sam Ade Jacobs +6
Zero Redundancy Optimizer (ZeRO) has been used to train a wide range of large language models on massive GPUs clusters due to its ease of use, efficiency, and good scalability. How…
ZeRO-Infinity: Breaking the GPU Memory Wall for Extreme Scale Deep Learning
Samyam Rajbhandari, Olatunji Ruwase, Jeff Rasley +2
In the last three years, the largest dense deep learning models have grown over 1000x to reach hundreds of billions of parameters, while the GPU memory has only grown by 5x (16 GB…
ZeRO-Offload: Democratizing Billion-Scale Model Training
Jie Ren, Samyam Rajbhandari, Reza Yazdani Aminabadi +5
Large-scale model training has been a playing ground for a limited few requiring complex model refactoring and access to prohibitively expensive GPU clusters. ZeRO-Offload changes…
APMSqueeze: A Communication Efficient Adam-Preconditioned Momentum SGD Algorithm
Hanlin Tang, Shaoduo Gan, Samyam Rajbhandari +4
Adam is the important optimization algorithm to guarantee efficiency and accuracy for training many important tasks such as BERT and ImageNet. However, Adam is generally not compat…