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Ching-Hsiang Chu
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Publications
- 2020
- [j7]Ammar Ahmad Awan, Arpan Jain, Ching-Hsiang Chu, Hari Subramoni, Dhabaleswar K. Panda:
Communication Profiling and Characterization of Deep-Learning Workloads on Clusters With High-Performance Interconnects. IEEE Micro 40(1): 35-43 (2020) - [c21]Ching-Hsiang Chu, Pouya Kousha, Ammar Ahmad Awan, Kawthar Shafie Khorassani, Hari Subramoni, Dhabaleswar K. D. K. Panda:
NV-group: link-efficient reduction for distributed deep learning on modern dense GPU systems. ICS 2020: 6:1-6:12 - 2019
- [j6]Ammar Ahmad Awan, Karthik Vadambacheri Manian, Ching-Hsiang Chu, Hari Subramoni, Dhabaleswar K. Panda:
Optimized large-message broadcast for deep learning workloads: MPI, MPI+NCCL, or NCCL2? Parallel Comput. 85: 141-152 (2019) - [j5]Ching-Hsiang Chu, Xiaoyi Lu, Ammar Ahmad Awan, Hari Subramoni, Bracy Elton, Dhabaleswar K. Panda:
Exploiting Hardware Multicast and GPUDirect RDMA for Efficient Broadcast. IEEE Trans. Parallel Distributed Syst. 30(3): 575-588 (2019) - [c19]Ammar Ahmad Awan, Jeroen Bédorf, Ching-Hsiang Chu, Hari Subramoni, Dhabaleswar K. Panda:
Scalable Distributed DNN Training using TensorFlow and CUDA-Aware MPI: Characterization, Designs, and Performance Evaluation. CCGRID 2019: 498-507 - [c16]Ammar Ahmad Awan, Arpan Jain, Ching-Hsiang Chu, Hari Subramoni, Dhabaleswar K. Panda:
Communication Profiling and Characterization of Deep Learning Workloads on Clusters with High-Performance Interconnects. Hot Interconnects 2019: 49-53 - [c14]Karthik Vadambacheri Manian, Ching-Hsiang Chu, Ammar Ahmad Awan, Kawthar Shafie Khorassani, Hari Subramoni:
OMB-UM: Design, Implementation, and Evaluation of CUDA Unified Memory Aware MPI Benchmarks. PMBS@SC 2019: 82-92 - 2018
- [c12]Ammar Ahmad Awan, Ching-Hsiang Chu, Hari Subramoni, Xiaoyi Lu, Dhabaleswar K. Panda:
OC-DNN: Exploiting Advanced Unified Memory Capabilities in CUDA 9 and Volta GPUs for Out-of-Core DNN Training. HiPC 2018: 143-152 - [c10]Ammar Ahmad Awan, Ching-Hsiang Chu, Hari Subramoni, Dhabaleswar K. Panda:
Optimized Broadcast for Deep Learning Workloads on Dense-GPU InfiniBand Clusters: MPI or NCCL? EuroMPI 2018: 2:1-2:9 - [i2]Ammar Ahmad Awan, Jeroen Bédorf, Ching-Hsiang Chu, Hari Subramoni, Dhabaleswar K. Panda:
Scalable Distributed DNN Training using TensorFlow and CUDA-Aware MPI: Characterization, Designs, and Performance Evaluation. CoRR abs/1810.11112 (2018) - 2017
- [c8]Ching-Hsiang Chu, Xiaoyi Lu, Ammar Ahmad Awan, Hari Subramoni, Jahanzeb Maqbool Hashmi, Bracy Elton, Dhabaleswar K. Panda:
Efficient and Scalable Multi-Source Streaming Broadcast on GPU Clusters for Deep Learning. ICPP 2017: 161-170 - [i1]Ammar Ahmad Awan, Ching-Hsiang Chu, Hari Subramoni, Dhabaleswar K. Panda:
Optimized Broadcast for Deep Learning Workloads on Dense-GPU InfiniBand Clusters: MPI or NCCL? CoRR abs/1707.09414 (2017) - 2016
- [j3]Khaled Hamidouche, Akshay Venkatesh, Ammar Ahmad Awan, Hari Subramoni, Ching-Hsiang Chu, Dhabaleswar K. Panda:
CUDA-Aware OpenSHMEM: Extensions and Designs for High Performance OpenSHMEM on GPU Clusters. Parallel Comput. 58: 27-36 (2016) - [c7]Ching-Hsiang Chu, Khaled Hamidouche, Akshay Venkatesh, Ammar Ahmad Awan, Dhabaleswar K. Panda:
CUDA Kernel Based Collective Reduction Operations on Large-scale GPU Clusters. CCGrid 2016: 726-735 - 2015
- [c3]Khaled Hamidouche, Akshay Venkatesh, Ammar Ahmad Awan, Hari Subramoni, Ching-Hsiang Chu, Dhabaleswar K. Panda:
Exploiting GPUDirect RDMA in Designing High Performance OpenSHMEM for NVIDIA GPU Clusters. CLUSTER 2015: 78-87 - [c2]A. A. Awan, Khaled Hamidouche, Ching-Hsiang Chu, Dhabaleswar K. Panda:
A Case for Non-blocking Collectives in OpenSHMEM: Design, Implementation, and Performance Evaluation using MVAPICH2-X. OpenSHMEM 2015: 69-86
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