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07/24/2023
PUMA: Secure Inference of LLaMA-7B in Five Minutes
With ChatGPT as a representative, tons of companies have began to provid...
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11/10/2022
A Comprehensive Survey on Distributed Training of Graph Neural Networks
Graph neural networks (GNNs) have been demonstrated to be a powerful alg...
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10/05/2022
GLM-130B: An Open Bilingual Pre-trained Model
We introduce GLM-130B, a bilingual (English and Chinese) pre-trained lan...
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07/20/2022
Mixed-Precision Inference Quantization: Radically Towards Faster inference speed, Lower Storage requirement, and Lower Loss
Based on the model's resilience to computational noise, model quantizati...
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04/28/2022
Programming Matrices as Staged Sparse Rows to Generate Efficient Matrix-free Differential Equation Solver
Solving differential equations is a critical task in scientific computin...
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03/17/2022
Canvas: Isolated and Adaptive Swapping for Multi-Applications on Remote Memory
Remote memory techniques for datacenter applications have recently gaine...
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02/10/2022
Quantization in Layer's Input is Matter
In this paper, we will show that the quantization in layer's input is mo...
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04/21/2021
GraphTheta: A Distributed Graph Neural Network Learning System With Flexible Training Strategy
Graph neural networks (GNNs) have been demonstrated as a powerful tool f...
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01/18/2021
DFOGraph: An I/O- and Communication-Efficient System for Distributed Fully-out-of-Core Graph Processing
With the magnitude of graph-structured data continually increasing, grap...
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09/20/2020
TADOC: Text Analytics Directly on Compression
This article provides a comprehensive description of Text Analytics Dire...
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08/17/2020
AIPerf: Automated machine learning as an AI-HPC benchmark
The plethora of complex artificial intelligence (AI) algorithms and avai...
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04/02/2020
RisGraph: A Real-Time Streaming System for Evolving Graphs
Graphs in the real world are constantly changing and of large scale. In ...
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10/13/2019
LiveGraph: A Transactional Graph Storage System with Purely Sequential Adjacency List Scans
The specific characteristics of graph workloads make it hard to design a...
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11/15/2017
Bridging the Gap Between Neural Networks and Neuromorphic Hardware with A Neural Network Compiler
Different from training common neural networks (NNs) for inference on ge...
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10/08/2016
SaberLDA: Sparsity-Aware Learning of Topic Models on GPUs
Latent Dirichlet Allocation (LDA) is a popular tool for analyzing discre...
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10/29/2015