Cover Image

Heimdall++: Optimizing GPU Utilization and Pipeline Parallelism for Efficient Single-Pulse Detection

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Xia, Bingzheng, Ren, Zujie, Ma, Kuang, Li, Xiaoqian, Li, Wenda, He, Shuibing
Format:	Preprint
Published:	2025
Subjects:	Distributed, Parallel, and Cluster Computing
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

SiPipe: Bridging the CPU-GPU Utilization Gap for Efficient Pipeline-Parallel LLM Inference
by: He, Yongchao, et al.
Published: (2025)

Frenzy: A Memory-Aware Serverless LLM Training System for Heterogeneous GPU Clusters
by: Chang, Zihan, et al.
Published: (2024)

Synergistic Tensor and Pipeline Parallelism
by: Qi, Mengshi, et al.
Published: (2025)

PPipe: Efficient Video Analytics Serving on Heterogeneous GPU Clusters via Pool-Based Pipeline Parallelism
by: Kong, Z. Jonny, et al.
Published: (2025)

A Flexible Programmable Pipeline Parallelism Framework for Efficient DNN Training
by: Jiang, Lijuan, et al.
Published: (2025)

HopGNN: Boosting Distributed GNN Training Efficiency via Feature-Centric Model Migration
by: Chen, Weijian, et al.
Published: (2024)

JanusPipe: Efficient Pipeline Parallel Training for Machine Learning Interatomic Potentials
by: Wang, Hongyu, et al.
Published: (2026)

GRNND: A GPU-Parallel Relative NN-Descent Algorithm for Efficient Approximate Nearest Neighbor Graph Construction
by: Li, Xiang, et al.
Published: (2025)

Balancing Pipeline Parallelism with Vocabulary Parallelism
by: Yeung, Man Tsung, et al.
Published: (2024)

HARP: Orchestrating Automated Parallel Training on Heterogeneous GPU Clusters
by: Liang, Antian, et al.
Published: (2025)

EXaCTz: Guaranteed Extremum Graph and Contour Tree Preservation for Distributed- and GPU-Parallel Lossy Compression
by: Li, Yuxiao, et al.
Published: (2026)

Efficient Graph Embedding at Scale: Optimizing CPU-GPU-SSD Integration
by: Li, Zhonggen, et al.
Published: (2025)

MPipeMoE: Memory Efficient MoE for Pre-trained Models with Adaptive Pipeline Parallelism
by: Zhang, Zheng, et al.
Published: (2025)

SPPO:Efficient Long-sequence LLM Training via Adaptive Sequence Pipeline Parallel Offloading
by: Chen, Qiaoling, et al.
Published: (2025)

Optimizing the Variant Calling Pipeline Execution on Human Genomes Using GPU-Enabled Machines
by: Kumar, Ajay, et al.
Published: (2025)

Breaking the Memory Wall: A Study of I/O Patterns and GPU Memory Utilization for Hybrid CPU-GPU Offloaded Optimizers
by: Maurya, Avinash, et al.
Published: (2024)

Parallel Collaborative ADMM Privacy Computing and Adaptive GPU Acceleration for Distributed Edge Networks
by: Xia, Mengchun, et al.
Published: (2026)

Bandwidth-Aware and Cost-Efficient Pipeline Parallel Scheduling in Geo-Distributed LLM Training
by: Zhang, Han, et al.
Published: (2026)

APEX: Asynchronous Parallel CPU-GPU Execution for Online LLM Inference on Constrained GPUs
by: Fan, Jiakun, et al.
Published: (2025)

Communication-Efficient Serving for Video Diffusion Models with Latent Parallelism
by: Wu, Zhiyuan, et al.
Published: (2025)

Memory Efficient and Staleness Free Pipeline Parallel DNN Training Framework with Improved Convergence Speed
by: Dutta, Ankita, et al.
Published: (2025)

cuFastTuckerPlus: A Stochastic Parallel Sparse FastTucker Decomposition Using GPU Tensor Cores
by: Li, Zixuan, et al.
Published: (2024)

TiMePReSt: Time and Memory Efficient Pipeline Parallel DNN Training with Removed Staleness
by: Dutta, Ankita, et al.
Published: (2024)

Nesterov Method for Asynchronous Pipeline Parallel Optimization
by: Ajanthan, Thalaiyasingam, et al.
Published: (2025)

AdaPtis: Reducing Pipeline Bubbles with Adaptive Pipeline Parallelism on Heterogeneous Models
by: Guo, Jihu, et al.
Published: (2025)

Adaptra: Straggler-Resilient Hybrid-Parallel Training with Pipeline Adaptation
by: Wu, Tianyuan, et al.
Published: (2025)

Seq1F1B: Efficient Sequence-Level Pipeline Parallelism for Large Language Model Training
by: Sun, Ao, et al.
Published: (2024)

Enhancing Memory Efficiency in Large Language Model Training Through Chronos-aware Pipeline Parallelism
by: Lin, Xinyuan, et al.
Published: (2025)

GPU-Based Parallel Computing Methods for Medical Photoacoustic Image Reconstruction
by: Yi, Xinyao, et al.
Published: (2024)

Concurrent Scheduling of High-Level Parallel Programs on Multi-GPU Systems
by: Knorr, Fabian, et al.
Published: (2025)

Neutron particle transport 3D method of characteristic Multi GPU platform Parallel Computing
by: Zhou, Faguo, et al.
Published: (2025)

A Preliminary Study on Accelerating Simulation Optimization with GPU Implementation
by: He, Jinghai, et al.
Published: (2024)

ZEUS: An Efficient GPU Optimization Method Integrating PSO, BFGS, and Automatic Differentiation
by: Soos, Dominik, et al.
Published: (2026)

GPU Memory and Utilization Estimation for Training-Aware Resource Management: Opportunities and Limitations
by: Yousefzadeh-Asl-Miandoab, Ehsan, et al.
Published: (2026)

DawnPiper: A Memory-scablable Pipeline Parallel Training Framework
by: Peng, Xuan, et al.
Published: (2025)

Parallelizing Drug Discovery: HPC Pipelines for Alzheimer's Molecular Docking and Simulation
by: Alliata, Paul Ruiz, et al.
Published: (2025)

Hetis: Serving LLMs in Heterogeneous GPU Clusters with Fine-grained and Dynamic Parallelism
by: Mo, Zizhao, et al.
Published: (2025)

Multi-GPU Acceleration of PALABOS Fluid Solver using C++ Standard Parallelism
by: Latt, Jonas, et al.
Published: (2025)

Parallel GPU-Enabled Algorithms for SpGEMM on Arbitrary Semirings with Hybrid Communication
by: McFarland, Thomas, et al.
Published: (2025)

Improving GPU Multi-Tenancy Through Dynamic Multi-Instance GPU Reconfiguration
by: Wang, Tianyu, et al.
Published: (2024)