2 citations · 6 across the 16 of their papers we have counts for
3 papers · 1 filter
Flover: A Temporal Fusion Framework for Efficient Autoregressive Model Parallel Inference
Jinghan Yao, Nawras Alnaasan, Tian Chen +4
Autoregressive models, despite their commendable performance in a myriad of generative tasks, face challenges stemming from their inherently sequential structure. Inference on thes…
MCR-DL: Mix-and-Match Communication Runtime for Deep Learning
Quentin Anthony, Ammar Ahmad Awan, Jeff Rasley +5
In recent years, the training requirements of many state-of-the-art Deep Learning (DL) models have scaled beyond the compute and memory capabilities of a single processor, and nece…
Performance Characterization of using Quantization for DNN Inference on Edge Devices: Extended Version
Hyunho Ahn, Tian Chen, Nawras Alnaasan +5
Quantization is a popular technique used in Deep Neural Networks (DNN) inference to reduce the size of models and improve the overall numerical performance by exploiting native har…