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Found 4 papers, 2 papers with code
PipeFusion: Displaced Patch Pipeline Parallelism for Inference of Diffusion Transformer Models
This paper introduces PipeFusion, a novel approach that harnesses multi-GPU parallelism to address the high computational and latency challenges of generating high-resolution images with diffusion transformers (DiT) models.
Exploring the Impact of In-Browser Deep Learning Inference on Quality of User Experience and Performance
Additionally, we noticed that in-browser inference increases the time it takes for graphical user interface (GUI) components to load in web browsers by a significant 67. 2\%, which severely impacts the overall QoE for users of web applications that depend on this technology.
BiBench: Benchmarking and Analyzing Network Binarization
Network binarization emerges as one of the most promising compression approaches offering extraordinary computation and memory savings by minimizing the bit-width.
Informative Sample-Aware Proxy for Deep Metric Learning
Among various supervised deep metric learning methods proxy-based approaches have achieved high retrieval accuracies.
