Cover Image

Noise-Aware Optimization in Nominally Identical Manufacturing and Measuring Systems for High-Throughput Parallel Workflows

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Schenk, Christina, Hernández-del-Valle, Miguel, Calero-Lumbreras, Luis, Noack, Marcus, Haranczyk, Maciej
Format:	Preprint
Published:	2025
Subjects:	Distributed, Parallel, and Cluster Computing Materials Science Machine Learning Optimization and Control Computation
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

A Simulated Annealing Approach to Identical Parallel Machine Scheduling
by: Li, Jiaxing, et al.
Published: (2024)

Decentralized Nonconvex Optimization under Heavy-Tailed Noise: Normalization and Optimal Convergence
by: Yu, Shuhua, et al.
Published: (2025)

From Sequential to Parallel: Reformulating Dynamic Programming as GPU Kernels for Large-Scale Stochastic Combinatorial Optimization
by: Zhao, Jingyi, et al.
Published: (2026)

Smoothed Gradient Clipping and Error Feedback for Decentralized Optimization under Symmetric Heavy-Tailed Noise
by: Yu, Shuhua, et al.
Published: (2023)

Optimizing STAR Aligner for High Throughput Computing in the Cloud
by: Kica, Piotr, et al.
Published: (2024)

Boosting Blockchain Throughput: Parallel EVM Execution with Asynchronous Storage for Reddio
by: Qi, Xiaodong, et al.
Published: (2025)

Shift Parallelism: Low-Latency, High-Throughput LLM Inference for Dynamic Workloads
by: Hidayetoglu, Mert, et al.
Published: (2025)

Provable Model-Parallel Distributed Principal Component Analysis with Parallel Deflation
by: Liao, Fangshuo, et al.
Published: (2025)

WOW: Workflow-Aware Data Movement and Task Scheduling for Dynamic Scientific Workflows
by: Lehmann, Fabian, et al.
Published: (2025)

Accelerating Cloud-Based Transcriptomics: Performance Analysis and Optimization of the STAR Aligner Workflow
by: Kica, Piotr, et al.
Published: (2025)

TD-Pipe: Temporally-Disaggregated Pipeline Parallelism Architecture for High-Throughput LLM Inference
by: Zhang, Hongbin, et al.
Published: (2025)

SmartQC: An Extensible DLT-Based Framework for Trusted Data Workflows in Smart Manufacturing
by: McGibney, Alan, et al.
Published: (2024)

Parallel Reduced Order Modeling for Digital Twins using High-Performance Computing Workflows
by: de Parga, S. Ares, et al.
Published: (2024)

Carbon-Aware Mapping and Scheduling for Deadline-Constrained Workflows
by: Schweisgut, Dominik, et al.
Published: (2026)

Exploring the Potential of Carbon-Aware Execution for Scientific Workflows
by: West, Kathleen, et al.
Published: (2025)

Activations and Gradients Compression for Model-Parallel Training
by: Rudakov, Mikhail, et al.
Published: (2024)

FATE: Future-State-Aware Scheduling for Heterogeneous LLM Workflows
by: Huang, Zirui, et al.
Published: (2026)

Carbon-Aware Workflow Scheduling with Fixed Mapping and Deadline Constraint
by: Schweisgut, Dominik, et al.
Published: (2025)

Cortex: Workflow-Aware Resource Pooling and Scheduling for Agentic Serving
by: Pagonas, Nikos, et al.
Published: (2025)

OptPipe: Memory- and Scheduling-Optimized Pipeline Parallelism for LLM Training
by: Li, Hongpei, et al.
Published: (2025)

A Systematic Evaluation of the Potential of Carbon-Aware Execution for Scientific Workflows
by: West, Kathleen, et al.
Published: (2025)

Load Balancing with Network Latencies via Distributed Gradient Descent
by: Balseiro, Santiago R., et al.
Published: (2025)

An Optimistic Gradient Tracking Method for Distributed Minimax Optimization
by: Huang, Yan, et al.
Published: (2025)

Tailoring Gradient Methods for Differentially-Private Distributed Optimization
by: Wang, Yongqiang, et al.
Published: (2022)

A First-Order Algorithm for Decentralised Min-Max Problems
by: Malitsky, Yura, et al.
Published: (2023)

Problem-Parameter-Free Decentralized Nonconvex Stochastic Optimization
by: Li, Jiaxiang, et al.
Published: (2024)

Temporal Parallelisation of the HJB Equation and Continuous-Time Linear Quadratic Control
by: Särkkä, Simo, et al.
Published: (2022)

Decentralized Distributed Optimization for Saddle Point Problems
by: Rogozin, Alexander, et al.
Published: (2021)

Decentralized Nonsmooth Nonconvex Optimization with Client Sampling
by: Chen, Xinyan, et al.
Published: (2026)

Non-ergodic linear convergence property of the delayed gradient descent under the strongly convexity and the Polyak-Łojasiewicz condition
by: Choi, Hyung Jun, et al.
Published: (2023)

Distributed Stochastic Momentum Tracking with Local Updates: Achieving Optimal Communication and Iteration Complexities
by: Huang, Kun, et al.
Published: (2025)

Krylov Solvers for Interior Point Methods with Applications in Radiation Therapy and Support Vector Machines
by: Liu, Felix, et al.
Published: (2023)

Accelerating Optimal Power Flow with GPUs: SIMD Abstraction of Nonlinear Programs and Condensed-Space Interior-Point Methods
by: Shin, Sungho, et al.
Published: (2023)

Distributed Constraint-Coupled Optimization: Harnessing ADMM-consensus for robustness
by: Messilem, Mohamed Abdelmouamin, et al.
Published: (2025)

Large-Scale LLM Inference with Heterogeneous Workloads: Prefill-Decode Contention and Asymptotically Optimal Control
by: Lin, Ruihan, et al.
Published: (2026)

An efficient implementation of parallel simulated annealing algorithm in GPUs
by: Ferreiro, A. M., et al.
Published: (2024)

One-Point Feedback for Composite Optimization with Applications to Distributed and Federated Learning
by: Beznosikov, Aleksandr, et al.
Published: (2021)

Modeling Task Mapping for Data-intensive Applications in Heterogeneous Systems
by: Wilhelm, Martin, et al.
Published: (2022)

A GPU-Accelerated Distributed Algorithm for Optimal Power Flow in Distribution Systems
by: Ryu, Minseok, et al.
Published: (2025)

Decentralized Gradient-Free Methods for Stochastic Non-Smooth Non-Convex Optimization
by: Lin, Zhenwei, et al.
Published: (2023)