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Found 4 papers, 2 papers with code
Any-Precision LLM: Low-Cost Deployment of Multiple, Different-Sized LLMs
Recently, considerable efforts have been directed towards compressing Large Language Models (LLMs), which showcase groundbreaking capabilities across diverse applications but entail significant deployment costs due to their large sizes.
Ginex: SSD-enabled Billion-scale Graph Neural Network Training on a Single Machine via Provably Optimal In-memory Caching
Thus, we propose Ginex, the first SSD-based GNN training system that can process billion-scale graph datasets on a single machine.
L3: Accelerator-Friendly Lossless Image Format for High-Resolution, High-Throughput DNN Training
The decoding process of L3 is effectively parallelized on the accelerator, thus minimizing CPU intervention for data preparation during DNN training.
A$^3$: Accelerating Attention Mechanisms in Neural Networks with Approximation
The attention mechanism is widely adopted by many state-of-the-art neural networks for computer vision, natural language processing, and machine translation, and accounts for a large portion of total execution time.
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