## +23 ## Back To Basics Algorithms ## KLAUS IGLBERGER ## 20 23 October 01 - 06 C++ Trainer/Consultant Author of “C++ Software Design” Chair of the CppCon Software Design track (Co-)Organizer of Implementations of the common data collections • Algorithms: work on the data contained in containers • Iterators: The glue between containers and algorithms ## The STL in a Nutshell ![Image](/uploads/d Implementations of the common data collections • Algorithms: work on the data contained in containers • Iterators: The glue between containers and algorithms ## Back To Basics - Iterators on Tuesday at 2pm

## CONSTRUCTING GENERIC ALGORITHMS ## algorithm noun al·go·rithm | \ 'al-gə-,ri-thəm ## Definition of algorithm : a procedure for solving a mathematical problem (as of finding the greatest common • Principles for algorithm design • Some holes in the standard • Ponters to further work ## ALGORITHMS: THE SOUL OF THE STL ![Image](/uploads/documents/7/3/4/9/7349bc689f62cb956becda260430bdd2/p3_1 "std::find_if". ## A WORD ABOUT RANGES "STL algorithms are not composable." -- Everyone (justifying ranges) ## A WORD ABOUT RANGES "STL algorithms are not composable." -- Everyone (justifying

## ADVANCED SIMD ALGORITHMS IN PICTURES Denis Yaroshevskiy ## THIS TALK • tinyurl.com/dycppcon2023 memcmp • copy_if • set intersection MEMCMP ## std::memcmp ## std::memcmp ![Image](/uploads/docum • tinyurl.com/dycppcon2023 • My First Simd • SIMD in C++20: EVE of a new Era • Advanced Simd Algorithms In Pictures, Meeting C++ • CppLang Slack, #simd Speaker notes

vec![3]); } #[test] fn pre_sorted() { 4/3/7 20:44 Rust算法教程 The Algos (algorithms) let mut arr = vec![0, 1, 2, 3, 4, 5, 6, 7, 8, 9]; odd_even_sort(&mut arr); assert_eq!(arr let mut v = vec![201, 127, 64, 37, 24, 4, 1]; } } 4/3/7 20:44 Rust算法教程 The Algos (algorithms) ```r radix_sort(&mut v); assert!(is_sorted(&v)); } #[test] fn ascending() { let "CARROT" ); assert_eq!( /3/7 20:44 Rust算法教程 The Algos (algorithms) inv_burrows_wheeler_transform(burrows_wheeler_transform("TOMATO".to_string)), "TOMATO"

sed malesuada diam lacus eget erat. ## Local phase Validate small neighborhoods with high-complexity algorithms. Describe neighborhood interactions coarsely in small tables. ## Global phase Collate the small tables into a big table of interactions. Validate the interactions with low-complexity algorithms. Indirect caller's interface fits many functions Function interface fits a specific function

## +21 ## GraphBLAS: Building a C++ Matrix API for Graph Algorithms BENJAMIN BROCK, SCOTT MCMILLAN 20 21 October 24-29 ## About Us  ## Ben, PhD Candidate at UC Berkeley Data structures and algorithms for parallel programs. Working on C++ library of distributed data structures. Please hire me!  ## Scott, Principal Engineer at CMU SEI Graph/ML/AI algorithms for large- and small-scale parallel systems. Working on GBTL, a linear algebra-based C++ library

## +23 ## Distributed Ranges: A Model for Building Distributed Data Structures, Algorithms, and Views ## BENJAMIN BROCK ## Notices and Disclaimers For notices, disclaimers, and details about performance Project Goals - Offer high-level, standard C++ distributed data structures - Support distributed algorithms Achieve high performance for both multi-GPU, NUMA, and multi-node execution float dot_produc Parallelism, Distributed Data Structures) - Distributed Ranges (Concepts) - Implementation (Algorithms and views) - Complex Data Structures (Dense and sparse matrices) - Lessons learned ## Outline

## CppCon 2023 Building bridges: Leveraging C++ and ROS for simulators, sensor data and algorithms Divya Aggarwal October 5, 2023 ## Need for Speed? Asphalt? GT? This is an autonomous driving simulator inputs. • We can take the example of testing and validation of perception algorithms for autonomous vehicles. - Perception algorithms process sensor data (from LiDAR, cameras) and perceive the environment and classifies the pedestrian in both the runs consistently. # Determinism with simulators and algorithms Simulation run 1: Camera image: [ Image 1] Detected pedestrians: [Pedestrian A, Pedestrian B]

# Design patterns for error handling in C++ programs using parallel algorithms and executors Mark Hoemmen $ ^{*} $ mhoemmen@stellarscience.com CppCon 2020 * hou'màn, or hœm'màn; he/him ## years post-PhD experience writing parallel C++ for science and engineering • Background: Parallel algorithms for big linear algebra problems • 1 $ ^{st} $ WG21: Nov 2017 • Started new job at Stellar Science Eschew raw pointers ## Outline • Parallelism makes error handling harder... • ...C++ parallel algorithms and tasks specifically • Message Passing Interface (MPI): 3 decades of distributed-memory parallel

v do not already exist in V(t), they are added to V(t+1). ## V ertex streams (not today) Some algorithms model graph streams a sequence of vertex events. A vertex stream consists of events that contain vertex and all of its neighbors. Although this model can enable a theoretical analysis of streaming algorithms, it cannot adequately model real-world unbounded streams, as the neighbors cannot be known in advance [Image](/uploads/documents/d/c/6/7/dc6753ffd7d6c085b81bf06b3e54c010/p30_2.jpg) compID = 6 • How can we run such algorithms if the graph is continuously generated as a stream of edges? • How can we perform iterative computation