Characterizing Compute-Communication Overlap in GPU-Accelerated Distributed Deep Learning: Performance and Power Implications
Fuente:
arXiv
Saved in:
| Main Authors: | Lee, Seonho, Oh, Jihwan, Kim, Junkyum, Go, Seokjin, Park, Jongse, Mahajan, Divya |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
MoETuner: Optimized Mixture of Expert Serving with Balanced Expert Placement and Token Routing
by: Go, Seokjin, et al.
Published: (2025)
by: Go, Seokjin, et al.
Published: (2025)
Characterizing the Efficiency of Distributed Training: A Power, Performance, and Thermal Perspective
by: Go, Seokjin, et al.
Published: (2025)
by: Go, Seokjin, et al.
Published: (2025)
ViBE: Co-Optimizing Workload Skew and Hardware Variability for MoE Serving
by: Go, Seokjin, et al.
Published: (2026)
by: Go, Seokjin, et al.
Published: (2026)
Lagom: Unleashing the Power of Communication and Computation Overlapping for Distributed LLM Training
by: Xu, Guanbin, et al.
Published: (2026)
by: Xu, Guanbin, et al.
Published: (2026)
Workload-Aware Hardware Accelerator Mining for Distributed Deep Learning Training
by: Adnan, Muhammad, et al.
Published: (2024)
by: Adnan, Muhammad, et al.
Published: (2024)
Syncopate: Efficient Multi-GPU AI Kernels via Automatic Chunk-Centric Compute-Communication Overlap
by: Qiang, Xinwei, et al.
Published: (2026)
by: Qiang, Xinwei, et al.
Published: (2026)
A GPU-Accelerated Distributed Algorithm for Optimal Power Flow in Distribution Systems
by: Ryu, Minseok, et al.
Published: (2025)
by: Ryu, Minseok, et al.
Published: (2025)
GPU-Accelerated Distributed QAOA on Large-scale HPC Ecosystems
by: Xu, Zhihao, et al.
Published: (2025)
by: Xu, Zhihao, et al.
Published: (2025)
Parallel Collaborative ADMM Privacy Computing and Adaptive GPU Acceleration for Distributed Edge Networks
by: Xia, Mengchun, et al.
Published: (2026)
by: Xia, Mengchun, et al.
Published: (2026)
Performance Characterization of Distributed Deep Learning Strategies: A Quantitative Evaluation of DDP, FSDP, and Parameter Server Architectures on GPU Clusters
by: Ovi, Md Sultanul Islam
Published: (2025)
by: Ovi, Md Sultanul Islam
Published: (2025)
Six Times to Spare: Characterizing GPU-Accelerated 5G LDPC Decoding for Edge-RSU Communications
by: Barker, Ryan, et al.
Published: (2026)
by: Barker, Ryan, et al.
Published: (2026)
NEST: Network- and Memory-Aware Device Placement For Distributed Deep Learning
by: Wang, Irene, et al.
Published: (2026)
by: Wang, Irene, et al.
Published: (2026)
Efficient Accelerated Graph Edit Distance Computation on GPU
by: Dabah, Adel, et al.
Published: (2026)
by: Dabah, Adel, et al.
Published: (2026)
AGAThA: Fast and Efficient GPU Acceleration of Guided Sequence Alignment for Long Read Mapping
by: Park, Seongyeon, et al.
Published: (2024)
by: Park, Seongyeon, et al.
Published: (2024)
Accelerating Intra-Node GPU-to-GPU Communication Through Multi-Path Transfers with CUDA Graphs
by: Sojoodi, Amirhossein, et al.
Published: (2026)
by: Sojoodi, Amirhossein, et al.
Published: (2026)
SOLANET: Distributed Neighbor Graph Construction on GPU-Accelerated Systems
by: Iwabuchi, Keita, et al.
Published: (2026)
by: Iwabuchi, Keita, et al.
Published: (2026)
LLMServingSim2.0: A Unified Simulator for Heterogeneous Hardware and Serving Techniques in LLM Infrastructure
by: Cho, Jaehong, et al.
Published: (2025)
by: Cho, Jaehong, et al.
Published: (2025)
Cross-region Model Training with Communication-Computation Overlapping and Delay Compensation
by: Zhu, Ying, et al.
Published: (2025)
by: Zhu, Ying, et al.
Published: (2025)
Characterizing the Performance of Accelerated Jetson Edge Devices for Training Deep Learning Models
by: K., Prashanthi S., et al.
Published: (2025)
by: K., Prashanthi S., et al.
Published: (2025)
gZCCL: Compression-Accelerated Collective Communication Framework for GPU Clusters
by: Huang, Jiajun, et al.
Published: (2023)
by: Huang, Jiajun, et al.
Published: (2023)
Dataflow-Oriented Classification and Performance Analysis of GPU-Accelerated Homomorphic Encryption
by: Nozaki, Ai, et al.
Published: (2026)
by: Nozaki, Ai, et al.
Published: (2026)
EarthSight: A Distributed Framework for Low-Latency Satellite Intelligence
by: Erol, Ansel Kaplan, et al.
Published: (2025)
by: Erol, Ansel Kaplan, et al.
Published: (2025)
CO2: Efficient Distributed Training with Full Communication-Computation Overlap
by: Sun, Weigao, et al.
Published: (2024)
by: Sun, Weigao, et al.
Published: (2024)
TokenWeave: Efficient Compute-Communication Overlap for Distributed LLM Inference
by: Gond, Raja, et al.
Published: (2025)
by: Gond, Raja, et al.
Published: (2025)
Distributed OpenMP Offloading of OpenMC on Intel GPU MAX Accelerators
by: Fridman, Yehonatan, et al.
Published: (2024)
by: Fridman, Yehonatan, et al.
Published: (2024)
Accelerating Biclique Counting on GPU
by: Qiu, Linshan, et al.
Published: (2024)
by: Qiu, Linshan, et al.
Published: (2024)
Lancet: Accelerating Mixture-of-Experts Training via Whole Graph Computation-Communication Overlapping
by: Jiang, Chenyu, et al.
Published: (2024)
by: Jiang, Chenyu, et al.
Published: (2024)
Modeling the Impact of Fiber Latency on Compute-Communication Overlap in Geo-Distributed Multi-Datacenter AI Training
by: Papavasileiou, Ioannis, et al.
Published: (2026)
by: Papavasileiou, Ioannis, et al.
Published: (2026)
MoE-Hub: Taming Software Complexity for Seamless MoE Overlap with Hardware-Accelerated Communication on Multi-GPU Systems
by: Zhou, Zhuoshan, et al.
Published: (2026)
by: Zhou, Zhuoshan, et al.
Published: (2026)
Evaluation of Programming Models and Performance for Stencil Computation on Current GPU Architectures
by: Shan, Baodi, et al.
Published: (2024)
by: Shan, Baodi, et al.
Published: (2024)
LLMServingSim: A HW/SW Co-Simulation Infrastructure for LLM Inference Serving at Scale
by: Cho, Jaehong, et al.
Published: (2024)
by: Cho, Jaehong, et al.
Published: (2024)
GPU Accelerated Sparse Cholesky Factorization
by: Karsavuran, M. Ozan, et al.
Published: (2024)
by: Karsavuran, M. Ozan, et al.
Published: (2024)
TileLink: Generating Efficient Compute-Communication Overlapping Kernels using Tile-Centric Primitives
by: Zheng, Size, et al.
Published: (2025)
by: Zheng, Size, et al.
Published: (2025)
A Study of Performance Programming of CPU, GPU accelerated Computers and SIMD Architecture
by: Yi, Xinyao
Published: (2024)
by: Yi, Xinyao
Published: (2024)
LLMServingSim 2.0: A Unified Simulator for Heterogeneous and Disaggregated LLM Serving Infrastructure
by: Cho, Jaehong, et al.
Published: (2026)
by: Cho, Jaehong, et al.
Published: (2026)
CRIUgpu: Transparent Checkpointing of GPU-Accelerated Workloads
by: Stoyanov, Radostin, et al.
Published: (2025)
by: Stoyanov, Radostin, et al.
Published: (2025)
GPU-Accelerated Batch-Dynamic Subgraph Matching
by: Qiu, Linshan, et al.
Published: (2024)
by: Qiu, Linshan, et al.
Published: (2024)
Understanding the Performance and Power of LLM Inferencing on Edge Accelerators
by: Arya, Mayank, et al.
Published: (2025)
by: Arya, Mayank, et al.
Published: (2025)
Performance Characterization of Containerized DNN Training and Inference on Edge Accelerators
by: K., Prashanthi S., et al.
Published: (2023)
by: K., Prashanthi S., et al.
Published: (2023)
Accelerating Sparse MTTKRP for Small Tensor Decomposition on GPU
by: Wijeratne, Sasindu, et al.
Published: (2025)
by: Wijeratne, Sasindu, et al.
Published: (2025)
Similar Items
-
MoETuner: Optimized Mixture of Expert Serving with Balanced Expert Placement and Token Routing
by: Go, Seokjin, et al.
Published: (2025) -
Characterizing the Efficiency of Distributed Training: A Power, Performance, and Thermal Perspective
by: Go, Seokjin, et al.
Published: (2025) -
ViBE: Co-Optimizing Workload Skew and Hardware Variability for MoE Serving
by: Go, Seokjin, et al.
Published: (2026) -
Lagom: Unleashing the Power of Communication and Computation Overlapping for Distributed LLM Training
by: Xu, Guanbin, et al.
Published: (2026) -
Workload-Aware Hardware Accelerator Mining for Distributed Deep Learning Training
by: Adnan, Muhammad, et al.
Published: (2024)