2.3k citations · 3k across the 20 of their papers we have counts for
20 papers
RecycleGPT: An Autoregressive Language Model with Recyclable Module
Yufan Jiang, Qiaozhi He, Xiaomin Zhuang +4
Existing large language models have to run K times to generate a sequence of K tokens. In this paper, we present RecycleGPT, a generative language model with fast decoding speed by…
Gaussian Boson Sampling with Pseudo-Photon-Number Resolving Detectors and Quantum Computational Advantage
Yu-Hao Deng, Yi-Chao Gu, Hua-Liang Liu +26
We report new Gaussian boson sampling experiments with pseudo-photon-number-resolving detection, which register up to 255 photon-click events. We consider partial photon distinguis…
Efficient Climate Simulation via Machine Learning Method
Xin Wang, Wei Xue, Yilun Han +1
Hybrid modeling combining data-driven techniques and numerical methods is an emerging and promising research direction for efficient climate simulation. However, previous works lac…
Lifetime-based Optimization for Simulating Quantum Circuits on a New Sunway Supercomputer
Yaojian Chen, Yong Liu, Xinmin Shi +8
High-performance classical simulator for quantum circuits, in particular the tensor network contraction algorithm, has become an important tool for the validation of noisy quantum…
Phase-Programmable Gaussian Boson Sampling Using Stimulated Squeezed Light
Han-Sen Zhong, Yu-Hao Deng, Jian Qin +23
The tantalizing promise of quantum computational speedup in solving certain problems has been strongly supported by recent experimental evidence from a high-fidelity 53-qubit super…
Quantum computational advantage using photons
Han-Sen Zhong, Hui Wang, Yu-Hao Deng +21
Gaussian boson sampling exploits squeezed states to provide a highly efficient way to demonstrate quantum computational advantage. We perform experiments with 50 input single-mode…
Benchmarking 50-Photon Gaussian Boson Sampling on the Sunway TaihuLight
Yuxuan Li, Mingcheng Chen, Yaojian Chen +6
Boson sampling is expected to be one of an important milestones that will demonstrate quantum supremacy. The present work establishes the benchmarking of Gaussian boson sampling (G…
Model-based Adversarial Meta-Reinforcement Learning
Zichuan Lin, Garrett Thomas, Guangwen Yang +1
Meta-reinforcement learning (meta-RL) aims to learn from multiple training tasks the ability to adapt efficiently to unseen test tasks. Despite the success, existing meta-RL algori…
Distributional Reward Decomposition for Reinforcement Learning
Zichuan Lin, Li Zhao, Derek Yang +3
Many reinforcement learning (RL) tasks have specific properties that can be leveraged to modify existing RL algorithms to adapt to those tasks and further improve performance, and…
Massively Scaling Seismic Processing on Sunway TaihuLight Supercomputer
Yongmin Hu, Hailong Yang, Zhongzhi Luan +1
Common Midpoint (CMP) and Common Reflection Surface (CRS) are widely used methods for improving the signal-to-noise ratio in the field of seismic processing. These methods are comp…
Implementation and Performance of Barnes-Hut N-body algorithm on Extreme-scale Heterogeneous Many-core Architectures
Masaki Iwasawa, Daisuke Namekata, Ryo Sakamoto +9
In this paper, we report the implementation and measured performance of our extreme-scale global simulation code on Sunway TaihuLight and two PEZY-SC2 systems: Shoubu System B and…
An Adaptive Remote Stochastic Gradient Method for Training Neural Networks
Yushu Chen, Hao Jing, Wenlai Zhao +5
We present the remote stochastic gradient (RSG) method, which computes the gradients at configurable remote observation points, in order to improve the convergence rate and suppres…
swTVM: Towards Optimized Tensor Code Generation for Deep Learning on Sunway Many-Core Processor
Mingzhen Li, Changxi Liu, Jianjin Liao +8
The flourish of deep learning frameworks and hardware platforms has been demanding an efficient compiler that can shield the diversity in both software and hardware in order to pro…
swCaffe: a Parallel Framework for Accelerating Deep Learning Applications on Sunway TaihuLight
Jiarui Fang, Liandeng Li, Haohuan Fu +5
This paper reports our efforts on swCaffe, a highly efficient parallel framework for accelerating deep neural networks (DNNs) training on Sunway TaihuLight, the current fastest sup…
Quantum Teleportation-Inspired Algorithm for Sampling Large Random Quantum Circuits
Ming-Cheng Chen, Riling Li, Lin Gan +4
We show that low-depth random quantum circuits can be efficiently simulated by a quantum teleportation-inspired algorithm. By using logical qubits to redirect and teleport the quan…
Working Principles of Binary Differential Evolution
Benjamin Doerr, Weijie Zheng
We conduct a first fundamental analysis of the working principles of binary differential evolution (BDE), an optimization heuristic for binary decision variables that was derived b…
RedSync : Reducing Synchronization Traffic for Distributed Deep Learning
Jiarui Fang, Haohuan Fu, Guangwen Yang +1
Data parallelism has become a dominant method to scale Deep Neural Network (DNN) training across multiple nodes. Since synchronizing a large number of gradients of the local model…
Episodic Memory Deep Q-Networks
Zichuan Lin, Tianqi Zhao, Guangwen Yang +1
Reinforcement learning (RL) algorithms have made huge progress in recent years by leveraging the power of deep neural networks (DNN). Despite the success, deep RL algorithms are kn…
Quantum Supremacy Circuit Simulation on Sunway TaihuLight
Riling Li, Bujiao Wu, Mingsheng Ying +2
With the rapid progress made by industry and academia, quantum computers with dozens of qubits or even larger size are being realized. However, the fidelity of existing quantum com…
Cavs: A Vertex-centric Programming Interface for Dynamic Neural Networks
Hao Zhang, Shizhen Xu, Graham Neubig +4
Recent deep learning (DL) models have moved beyond static network architectures to dynamic ones, handling data where the network structure changes every example, such as sequences…