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20192026
most citedOliVe: Accelerating Large Language Models via Hardware-friendly Outlier-Victim Pair Quantization

150 citations · 310 across the 71 of their papers we have counts for

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Showing 2024Show all

10 papers · 1 filter

cs.CR2024

Nimbus: Secure and Efficient Two-Party Inference for Transformers

Zhengyi Li, Kang Yang, Jin Tan +8

Transformer models have gained significant attention due to their power in machine learning tasks. Their extensive deployment has raised concerns about the potential leakage of sen…

cs.CV2024

SparseTem: Boosting the Efficiency of CNN-Based Video Encoders by Exploiting Temporal Continuity

Kunyun Wang, Shuo Yang, Jieru Zhao +4

Deep learning models have become pivotal in the field of video processing and is increasingly critical in practical applications such as autonomous driving and object detection. Al…

quant-ph2024

Design the Quantum Instruction Set with the Cartan Coordinate Analysis Framework

Anbang Wu, Jingwen Leng, Minyi Guo

Most quantum compiling efforts rely on standard two-qubit basis gates, such as CX and iSWAP, to implement general quantum operations. However, with the advancement of quantum archi…

cs.DC2024

Vortex: Efficient Sample-Free Dynamic Tensor Program Optimization via Hardware-aware Strategy Space Hierarchization

Yangjie Zhou, Honglin Zhu, Qian Qiu +9

Dynamic-shape deep neural networks (DNNs) are rapidly evolving, attracting attention for their ability to handle variable input sizes in real-time applications. However, existing c…

cs.AR2024

Potamoi: Accelerating Neural Rendering via a Unified Streaming Architecture

Yu Feng, Weikai Lin, Zihan Liu +6

Neural Radiance Field (NeRF) has emerged as a promising alternative for photorealistic rendering. Despite recent algorithmic advancements, achieving real-time performance on today'…

cs.DC2024

vTensor: Flexible Virtual Tensor Management for Efficient LLM Serving

Jiale Xu, Rui Zhang, Cong Guo +11

Large Language Models (LLMs) are widely used across various domains, processing millions of daily requests. This surge in demand poses significant challenges in optimizing throughp…

cs.DC2024

Towards Fast Setup and High Throughput of GPU Serverless Computing

Han Zhao, Weihao Cui, Quan Chen +6

Integrating GPUs into serverless computing platforms is crucial for improving efficiency. However, existing solutions for GPU-enabled serverless computing platforms face two signif…

cs.AR2024★ 1 cited

Cicero: Addressing Algorithmic and Architectural Bottlenecks in Neural Rendering by Radiance Warping and Memory Optimizations

Yu Feng, Zihan Liu, Jingwen Leng +2

Neural Radiance Field (NeRF) is widely seen as an alternative to traditional physically-based rendering. However, NeRF has not yet seen its adoption in resource-limited mobile syst…

cs.DC2024

Accelerating Sparse DNNs Based on Tiled GEMM

Cong Guo, Fengchen Xue, Jingwen Leng +5

Network pruning can reduce the computation cost of deep neural network (DNN) models. However, sparse models often produce randomly-distributed weights to maintain accuracy, leading…

cs.DC2024★ 1 cited

GMLake: Efficient and Transparent GPU Memory Defragmentation for Large-scale DNN Training with Virtual Memory Stitching

Cong Guo, Rui Zhang, Jiale Xu +8

Large-scale deep neural networks (DNNs), such as large language models (LLMs), have revolutionized the artificial intelligence (AI) field and become increasingly popular. However,…