Scientific Unit Testing Dave Steffen, Ph.D. Software Lead in Physics which is relevant dsteffen@scitec.com www.scitec.com 1If I have seen further than others, it is by standing upon the shoulders Limit tests to the code in question 26Reproducibility (handling nondeterministic results) Most scientific experiments have measurement error or noise. Interference from the environment: noisy signals correct Unit tests attempt to show !C Confidence in C tracks thoroughness of tests A.K.A "The Scientific Method" 42Acknowledgements Kris Jusiak, Quantlab Financial Check out his C++20 macro-free unit

1 SCIENCE PASSION TECHNOLOGY Introduction to Scientific Writing 01 Structure of Scientific Papers Matthias Boehm Graz University of Technology, Austria Institute of Interactive Systems and Data Science Engineering BMK endowed chair for Data Management Last update: Oct 23, 2021 2 706.015 Introduction to Scientific Writing – 01 Introduction and Overview Matthias Boehm, Graz University of Technology, WS 2020/21  Changes in WS20/21, now max constraints  Introduction to Scientific Writing ISDS Group Boehm 40/40 3 706.015 Introduction to Scientific Writing – 01 Introduction and Overview Matthias Boehm, Graz

1 SCIENCE PASSION TECHNOLOGY Introduction to Scientific Writing 02 Scientific Reading and Writing Matthias Boehm Graz University of Technology, Austria Institute of Interactive Systems and Data Science endowed chair for Data Management Last update: Nov 04, 2021 2 706.015 Introduction to Scientific Writing – 02 Scientific Reading and Writing Matthias Boehm, Graz University of Technology, WS 2021/22 Announcements/Org WS20/21, now max constraints  Introduction to Scientific Writing ISDS Group Boehm 39/40 3 706.015 Introduction to Scientific Writing – 02 Scientific Reading and Writing Matthias Boehm, Graz University

Poster submission: Modern C++ for Parallelism in High Performance Computing Victor Eijkhout CppCon 2024 Introduction This poster reports on ‘D2D’, a benchmark that explores elegance of expression and and perfor- mance in the context of a High Performance Computing ‘mini-application’. The same code has been implemented using a number of different approaches to parallelism. Implementations are discussed discussed with performance results. Relevance C++ is making inroads into HPC / Scientific Computing, a field traditionally dominated by C and Fortran. With all the developments in modern C++ such as range

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1 SCIENCE PASSION TECHNOLOGY Introduction to Scientific Writing 03 Experiments & Reproducibility Matthias Boehm Graz University of Technology, Austria Institute of Interactive Systems and Data Science Engineering BMK endowed chair for Data Management Last update: Nov 11, 2021 2 706.015 Introduction to Scientific Writing – 03 Experiments & Reproducibility Matthias Boehm, Graz University of Technology, WS 2021/22 now max constraints  Introduction to Scientific Writing  #3 Timeline  Nov 11: project selection via email to m.boehm@tugraz.at (11.59pm) subject: [Scientific Writing] Project Selection  Dec 23:

Constraints Architecture Substitution Construction Conclusion Symbolic Calculus for High-Performance Computing from Scratch using C++23 Vincent Reverdy Laboratoire d’Annecy de Physique des Particules, France Symbolic Computation, Joël Falcou and Vincent Reverdy, CppCon 2019 Hypothesis This is the Scientific Computing Track so you all know about optimization, performance, parallelism, . . . What this talk is not about Complicated maths (you are smart people, you can do it yourself) High-performance computing (you all know about it + see the 2019 talk for that) Benchmarks, assembly, and optimization (see

connected and accessible information being supercharged by artificial intelligence, accelerating computing power, and semi-borderless capital…all driving massive change. Sport provides a good analogy for Enterprise Impact’ via Morgan Stanley (10/23) Enabling Infrastructure CPUs Big Data / Cloud GPUs Computing Cycles Over Time – 1960s-2020s, per Morgan Stanley Note: Axis is logarithmic; i.e., there are Estimates how much progress comes from bigger models versus smarter algorithms, based on how much computing power you'd need to reach top performance without any improvements. Source: Epoch AI (3/24) Impact

Wait GPU Work Preparation As general purpose computing involves, GPU starts to detach from rendering pipeline, and can be considered as an external computing resource. CPU can schedule compute tasks to Multiplication 16 Matrix multiplication is almost the fundamental compute unit for many modern scientific computation, it is also a classic performance improvement problem to solve. Example: Feedforward Multiplication 17 Matrix multiplication is almost the fundamental compute unit for many modern scientific computation, it is also a classic performance improvement problem to solve. Example: Feedforward

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