The new BaBar Data Reconstruction Control System
A. Ceseracciu, M. Piemontese, F. Safai Tehrani, P. Elmer, D. Johnson, T. M. Pulliam
Abstract
The BaBar experiment is characterized by extremely high luminosity, a complex detector, and a huge data volume, with increasing requirements each year. To fulfill these requirements a new control system has been designed and developed for the offline data reconstruction system. The new control system described in this paper provides the performance and flexibility needed to manage a large number of small computing farms, and takes full benefit of OO design. The infrastructure is well isolated from the processing layer, it is generic and flexible, based on a light framework providing message passing and cooperative multitasking. The system is actively distributed, enforces the separation between different processing tiers by using different naming domains, and glues them together by dedicated brokers. It provides a powerful Finite State Machine framework to describe custom processing models in a simple regular language. This paper describes this new control system, currently in use at SLAC and Padova on ~450 CPUs organized in 12 farms.
Create a lesson
Related papers
Workload-Static Optical Circuit Switching For Scalable LLM Inference Decode
Maximilian Thürmer, Nicolas Scotto di Perto, Eloise Stein et al.
Characterizing Serverless Workloads: A Large-Scale Analysis of Function-as-a-Service Platforms
Saman Akbari, Yassine Lazreg, Mohammadreza Malekabbasi et al.
ForgeKernel: Self-Evolving Kernels Catching and Surpassing Experts and Agents
Yaojian Chen, Dazhi Peng, Yiyun Zheng et al.
Local Distributed Computation under Crash Failures
Diana Ghinea, Fabian Kuhn, Chen-Da Liu-Zhang et al.
TapeSAC: Automated, Pareto-Optimal Fine-Grained Memory Management for Large Model Training
Kaihui Ren, Yifan Zhao, Zejian Wang et al.
Accelerating Offloading-Based MoE Inference by Interleaving Concurrent Requests
Hongseung Yu, In Gim, Kyunghan Lee et al.