We stand with Ukraine

We stand with Ukraine

Meng Hao

Orcid: 0000-0003-0043-4370

Affiliations:

Harbin Institute of Technology, School of Cyberspace Science, China (PhD 2020)

According to our database¹, Meng Hao authored at least 20 papers between 2016 and 2026.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of three.

Timeline

Legend:

Book In proceedings Article PhD thesis Dataset Other

Links

Online presence:

on orcid.org
on ieeexplore.ieee.org

On csauthors.net:

Bibliography

2026

A Multi-Level Acceleration Scheme for AI Model Training on ARM Architecture Processors.

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Concurr. Comput. Pract. Exp., March, 2026

Accelerating Secure Machine Learning Training on GPUs With Pipeline Parallelism.

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IEEE Trans. Dependable Secur. Comput., 2026

2025

HEngine: A High Performance Optimization Framework on a GPU for Homomorphic Encryption.

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ACM Trans. Archit. Code Optim., June, 2025

Dynamic Power Management Through Multi-agent Deep Reinforcement Learning for Heterogeneous Systems.

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ACM Trans. Archit. Code Optim., June, 2025

Deep Learning Workload Mapping Optimization on Jetson Platforms.

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ACM Trans. Archit. Code Optim., June, 2025

SEPPDL: A Secure and Efficient Privacy-Preserving Deep Learning Inference Framework for Autonomous Driving.

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ACM Trans. Auton. Adapt. Syst., March, 2025

DynGPU: A Dynamic GPU Sharing Framework for Enhanced Resource Utilization and Task Scheduling in Concurrent DNN Training.

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Proceedings of the 31th IEEE International Conference on Parallel and Distributed Systems, 2025

2024

Optimizing depthwise separable convolution on DCU.

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CCF Trans. High Perform. Comput., December, 2024

Model-Free GPU Online Energy Optimization.

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IEEE Trans. Sustain. Comput., 2024

DRLCAP: Runtime GPU Frequency Capping With Deep Reinforcement Learning.

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IEEE Trans. Sustain. Comput., 2024

Fast Memory Disaggregation with SwiftSwap.

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Proceedings of the Network and Parallel Computing, 2024

2022

Dynamic GPU Energy Optimization for Machine Learning Training Workloads.

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IEEE Trans. Parallel Distributed Syst., 2022

Online Power Management for Multi-Cores: A Reinforcement Learning Based Approach.

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IEEE Trans. Parallel Distributed Syst., 2022

2021

Fine-Grained Powercap Allocation for Power-Constrained Systems Based on Multi-Objective Machine Learning.

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Athanasios V. Vasilakos

IEEE Trans. Parallel Distributed Syst., 2021

Automatic translation of data parallel programs for heterogeneous parallelism through OpenMP offloading.

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J. Supercomput., 2021

2019

Automatic generation of benchmarks for I/O-intensive parallel applications.

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Laurence T. Yang

J. Parallel Distributed Comput., 2019

Multi-Parameter Performance Modeling Based on Machine Learning with Basic Block Features.

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Proceedings of the 2019 IEEE Intl Conf on Parallel & Distributed Processing with Applications, 2019

PROFPRED: A Compiler-Level IR Based Performance Prediction Framework for MPI Industrial Applications.

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Laurence Tianruo Yang

Proceedings of the 21st IEEE International Conference on High Performance Computing and Communications; 17th IEEE International Conference on Smart City; 5th IEEE International Conference on Data Science and Systems, 2019

2017

Predicting HPC parallel program performance based on LLVM compiler.

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Clust. Comput., 2017

2016

Communication optimization for RDMA-based science data transmission tools.

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J. Supercomput., 2016

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