Time Series Mining at Petascale Performance

Raoofy, Amir; Karlstetter, Roman; Yang, Dazhong; Trinitis, Carsten; Schulz, Martin

doi:10.1007/978-3-030-50743-5_6

Cited by 5 publications

(3 citation statements)

References 20 publications

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“…In this project, students extend the implementation of a sinc interpolation function [18] with OpenMP as well as manual SIMD and evaluate their solutions on several CPU platforms in BEAST. (3) In the last project, students work on a time series mining application, specifically matrix profile computation [17]. We provide students with the source code for the serial implementation of matrix profile computation.…”

Section: The Lab Structure and Teaching Approachmentioning

confidence: 99%

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BEAST Lab: A Practical Course on Experimental Evaluation of Diverse Modern HPC Architectures and Accelerators

Raoofy,

Elis,

Bode

et al. 2024

JOCSE

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Giving students a good understanding how micro-architectural effects impact achievable performance of HPC workloads is essential for their education. It enables them to find effective optimization strategies and to reason about sensible approaches towards better efficiency. This paper describes a lab course held in collaboration between LRZ, LMU, and TUM. The course was born with a dual motivation in mind: filling a gap in educating students to become HPC experts, as well as understanding the stability and usability of emerging HPC programming models for recent CPU and GPU architectures with the help of students. We describe the course structure used to achieve these goals, resources made available to attract students, and experiences and statistics from running the course for six semesters. We conclude with an assessment of how successfully the lab course met the initially set vision.

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Section: The Lab Structure and Teaching Approachmentioning

confidence: 99%

“…The projects cover the same type of topics and experiments but need more effort in programming, enabling multi-threading and various optimizations such as low-level manual vectorization. These projects target a selection of conventional and fairly new applications such as multigrid solver [20], matrix profile computation [17], and interpolation kernels [18].…”

mentioning

confidence: 99%

BEAST Lab: A Practical Course on Experimental Evaluation of Diverse Modern HPC Architectures and Accelerators

Raoofy,

Elis,

Bode

et al. 2024

JOCSE

View full text Add to dashboard Cite

show abstract

“…Sorting is a fundamental problem in computer science and a critical building block for many types of applications such as, but not limited to, database servers [1], image rendering engines [2], mining of time series [3] or JPEG steganography with particle swarm [4]. This is why sorting algorithms have the attention of the research community intending to provide efficient sorting libraries on new architectures that could potentially leverage the performance of a wide range of software.…”

Section: Introductionmentioning

confidence: 99%