Prototyping Virtual Data Technologies in ATLAS Data Challenge 1 Production
A. Vaniachine, D. Malon, P. Nevski, K. De
Abstract
For efficiency of the large production tasks distributed worldwide, it is essential to provide shared production management tools comprised of integratable and interoperable services. To enhance the ATLAS DC1 production toolkit, we introduced and tested a Virtual Data services component. For each major data transformation step identified in the ATLAS data processing pipeline (event generation, detector simulation, background pile-up and digitization, etc) the Virtual Data Cookbook (VDC) catalogue encapsulates the specific data transformation knowledge and the validated parameters settings that must be provided before the data transformation invocation. To provide for local-remote transparency during DC1 production, the VDC database server delivered in a controlled way both the validated production parameters and the templated production recipes for thousands of the event generation and detector simulation jobs around the world, simplifying the production management solutions.
Create a lesson
Related papers
PixelFlow: Token-Level Workload Management for Efficient Distributed DiT Serving
Zhexiang Zhang, Minchen Yu, Yifan Sun et al.
A Kubernetes-Native Request Router for Quality-Aware Inference Serving in the Computing Continuum
Ignjat Karanovic, Pantelis A. Frangoudis, Ivan Čilić et al.
Accelerating Sharded Data Parallelism at Scale with Federated Learning
Gianluca Mittone, Marco Aldinucci
Distributed Edge Inference: an Experimental Study on Multiview Detection
Gianluca Mittone, Giulio Malenza, Marco Aldinucci et al.
P-GADMM: Parallel Group-Based ADMM for Asynchronous Optimization in Heterogeneous Edge Networks
Gaiguo Wei, Qingying Zhang, Heqiang Wang et al.
VERA: Reinforcement Learning for Dynamic Memory Scaling of HPC Workloads in Kubernetes
Ade Pramono, Jie Ren, Ivy Peng