The Go frontend for GCC Ian Lance Taylor Google iant@google.com Abstract A description of the Go language frontend for gcc. This is a new frontend which is a complete implementation of the new Go programming programming language. The frontend is currently some 50,000 lines of C++ code, and uses its own IR which is then converted to GENERIC. I describe the structure of the frontend and the IR, issues that arise arise when compiling the Go language, and issues with hook- ing up any frontend to the gcc middle-end. 1 Introduction Go is a new programming language designed by Robert Griesemer, Rob Pike, and Ken Thompson

1Can data-oriented-design be improved? Ollivier Roberge Collège Jean-de-Brébeuf 2A brief historic • 1960s • FORTRAN • Lisp • 1980s • OOP • Structured programming • Modules • 2000s • Template

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

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

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 Outline of an implementation Conclusion Going beyond End of story? No! Plenty of things can be improved This is the simplest possible integrator: can we do better and achieve more accuracy and precision Firsts steps Context Theoretical foundations Outline of an implementation Conclusion Toward an improved version Integration function (1/4) // Integrate the Friedmann −Lemaitre(−Robertson −Walker) equations

Nim - the first high performance Nim - the first high performance language with full support for hot code- language with full support for hot code- reloading at runtime reloading at runtime by Viktor 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 18 Simply Nim Simply Nim statically typed high performance (compiles to native binaries - comparable to C/C++) very clean & elegant - no, beauty is NOT subjective next big thing: - Andrei Alexandrescu Nim is one of the most logical paths forward on-par performance with C/C++ (compiles to them) some of the most easy interop with C/C++ ........ (compiles to them)

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 - things: ○ Deal with actual pointers and C++ data types ● The compiled program keeps most of the performance and dynamism of an interpreted language, and: ○ is now a C++ .so ○ is not an interpreted scriptCython

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