PERFORMANCE MATTERS (joint work with Charlie Curtsinger, Grinnell College) emeryberger.com, @emeryberger Emery Berger College of Information and Computer Sciences UMASS AMHERSTA short time ago : un.bmp Ogle is too slow! OGLE’84 is too slow!Transistors (millions) Clock Speed (MHz) Performance used to be easy 0.001 0.01 0.1 1 10 100 1,000 10,000 1970 1975 1980 1985 1990 1995 gle loading… No mojitos for me… Back to the present…Transistors (millions) Clock Speed (MHz) Performance not easy anymore 0.001 0.01 0.1 1 10 100 1,000 10,000 1970 1975 1980 1985 1990 1995

1 Quickly Testing Qt Desktop Applications with Approval Tests Clare Macrae (She/her) clare@claremacrae.co.uk 16 September 2020 CppCon (Online)2 Audience: Developers testing Desktop GUIs, including and readable with fixtures • ApprovalTests.Cpp.Qt feedback welcome!80 Quickly Test Qt Desktop Applications • All links from this talk, and more, via: – bit.ly/TestingQt – github.com/claremacrae/talks

Being Friendly to Your Hardware Performance Engineering A gentle introduction to hardware for software engineers 2Where does C++ run? 3On an abstract C++ machine 4On an abstract C++ machine? In most practical cases at boot time only Same capacity, different composition => different performance profile From JESD 79-4 DDR4 specificationMemory • Memory system is in the uncore • Cores act Multiple instructions resulting in fewer operations • ISA restrictions may have impact to performance Imaginary ARM mov r20, 0x123456789abcdef0Register renaming 52 Branching Fetch Decode Queue

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 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 with performance results. Relevance multi-dimensional arrays through ‘mdspan’, it is interesting to explore what C++ can offer for lower level performance critical operations. Scientific computing is an interesting test cases since many algorithms are

console.log(object.foo) Jonathan Müller A fast, compliant JSON pull parser for writing robust applications undefined Jonathan Müller — @foonathan Express your expectations CppCon 2023-10-03 10JSON parsing std::print("{}\n", object.at("foo")); Jonathan Müller A fast, compliant JSON pull parser for writing robust applications Uncaught exception. Jonathan Müller — @foonathan Express your expectations CppCon 2023-10-03

Introduction Firsts steps Context Theoretical foundations Outline of an implementation Conclusion High-Performance Numerical Integration in the Age of C++26 Vincent Reverdy Laboratoire d’Annecy de Physique des past, other languages do far better in terms of everything: functionality, ease of use, and even performance This talk The goal is NOT to revolutionize everything or show a library that beats everything yn+1 = yn + h s � i=1 biki ki = f � tn + cih, yn + h s � j=1 aijkj � , i = 1, . . . , s Performance concerns The Butcher Tableau can be very sparse Null coefficients should be optimized away Compilers

volume in terabytes ● Program analysis research and functional programming in a past life ● Love performance, software abstractions, and clean APIsWhy Python? ● Writing extensive APIs in Python - low boilerplate We’re at CppCon :) Why Python? Why C++?● Why? ○ Avoid reimplementing complex code for Python ○ Performance ○ Back and forth with user’s python code ○ Interoperability with data structures in Python - inform(); } }Dispatchers and callbacks ● Callbacks are a common theme in many dispatcher based applications ● Dispatching may happen in: ○ The main python thread, but blocked ○ A separate thread, thus

is moved into general-purpose registers for computations • Depending on the platform, may see a performance gain at this stageQuat Functions template inline

Binding 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 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 concepts Symbolic calculus (derivatives, integrals) Full blown custom rule-based rewriting High-performance Since formulas have the entire information on the mathematical AST, it’s possible to generate