Accelerating High-Energy Physics Data Analysis

The field of high-energy physics is experiencing a significant shift towards leveraging advanced computing technologies to accelerate data analysis. A key direction of this movement is the integration of near-data processing and specialized hardware, such as Data Processing Units (DPUs), to minimize data movement and reduce processing delays. This approach enables faster and more efficient data filtering, which is crucial for extracting relevant events from vast datasets. Additionally, the development of optimized computing facilities and platforms, such as those utilizing high-speed networking and managed storage systems, is also playing a critical role in advancing the field. Noteworthy papers in this area include SkimROOT, which demonstrates a 44.3× performance improvement in LHC data filtering, and SubMIT, which provides a powerful platform for interactive data analysis and large-scale processing.

Sources

SubMIT: A Physics Analysis Facility at MIT

Usability Evaluation of Cloud for HPC Applications

Analysis of Server Throughput For Managed Big Data Analytics Frameworks

SkimROOT: Accelerating LHC Data Filtering with Near-Storage Processing

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