mine, all mine! You can’t have them. Agenda 1. Current status of C++ safety: MISRA and C++ CG 2. Parallel Safety rules 3. Automotive Safety case Safety Critical API Evolution minimize API surface area no harm What is still missing? So far most only deal with Sequential code Very few deal with Parallel code Even fewer deal with Concurrent, event driven code None deal with Heterogeneous dispatch rules pulled from • C++CG • HIC++ • REphrase H2020 project • CERT C++ • JSF++ (no parallel rules) • WG23 (no parallel rules) • Added some from our own contributions • Many joined, average 5-8 per meeting

CurveBS I/O processing flow Before introducing IO processing flow, we first describe the overall architecture, data organization and topology structure of CURVE. CurveBS uses the central sockets. l Nebdserver: Accepts requests from NEBDClient and calls Curve Client for corresponding processing. it can receive requests from different NEBDClients.3. Through the above splitting, NebdClient NebdClient replaces Curve Client and directly interfaces with upper services. There is no logical processing in NEBDClient, it just proxy requests and has limited retries, which ensuring that NEBDClient

programs using parallel algorithms and executors Mark Hoemmen* mhoemmen@stellarscience.com CppCon 2020 * hoʊ’mən, or hœm’mən; he/himWho am I? • > 10 years post-PhD experience writing parallel C++ for for science and engineering • Background: Parallel algorithms for big linear algebra problems • 1st WG21: Nov 2017 • Started new job at Stellar Science in March Eschew raw pointersOutline • Parallelism Parallelism makes error handling harder… • …C++ parallel algorithms and tasks specifically • Message Passing Interface (MPI): 3 decades of distributed-memory parallel programming • MPI teaches design patterns

data-parallel types Dr. Matthias Kretz GSI Helmholtz Center for Heavy Ion Research CppCon ’23 @mkretz@floss.social github.com/mattkretzMotivation std::simd Overview Example: Image Processing Programming CppCon ’23 3 GSI Helmholtz Center for Heavy Ion ResearchMotivation std::simd Overview Example: Image Processing Programming Models Outlook Summary Motivation Motivation © by Matthias Kretz Matthias Kretz CppCon CppCon ’23 GSI Helmholtz Center for Heavy Ion ResearchMotivation std::simd Overview Example: Image Processing Programming Models Outlook Summary std::simd is for you! Matthias Kretz CppCon ’23 4 GSI Helmholtz

Seymour Cray pioneers pipelining ○ 1972 - CDC 8600 Multiprocessor ○ 1975 - Cray-1 pioneered vector processing (i.e. SIMD)Now for code...(almost) Let’s see our first mechanism for concurrent programming 37 using threads on your GPU for graphics ■ GPUs have 100s or 1000s of threads that are good for massively parallel tasks. ● (You could also use things like CUDA to take advantage of your graphics hardware) the sizes of files in a directory to find the total bytes of the files in a directory ■ i.e., a parallel wc tool ○ Each of those threads then needs to write to some ‘shared value’ to sum the total.

would be. So basic uses for it would be a chest, floor, walls, or if you wanted to use as much processing power you could, each individual part of a 3D model. MESH COLLIDERS: A Mesh Collider builds This is used in the FPS (First Person Shooter), RTS (Real Time Strategy), Action RPG, and MMORPG (Massively Multiplayer Online Role Playing Game) genres. I will call upon one of my favorite development studios (spawnWait < 0.05f) spawnWait = 0.05f; } } } IEnumerator is Unity’s version of parallel programming and it is supposed to be used in conjunction with StartCoRoutine. Zenva Academy

· · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · 143 3.4.5 Data processing · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · 143 · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · 906 7.1.5 Implementation of processing data changes · · · · · · · · · · · · · · · · · · · · · · · · 907 7.1.6 Unsupported scenarios· · · · · · · · · · · · · · · · · · · · · · · · 3064 13.7.13 Use TiDB Lightning to Import Data in Parallel · · · · · · · · · · · · · · · · · · · · 3066 13.7.14 TiDB Lightning Error Resolution · · · · ·

· · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · 113 3.4.5 Data processing · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · 113 · · · · · · · · · · · · · · · · · · · · · · · 2638 13.7.13 Use TiDB Lightning to Import Data in Parallel · · · · · · · · · · · · · · · · · · · · 2640 13.7.14 TiDB Lightning Error Resolution · · · · · Titanium) is an open-source distributed SQL database that supports Hybrid Transactional and Analytical Processing (HTAP) workloads. It is MySQL compatible and features horizontal scalability, strong consistency

removing the need to use short_paths in Windows. Note that the cache is still not concurrent, so parallel jobs or tasks should use independent caches. 2.13 New extensions plugins Several extension points libraries, binaries) from the build and source folder to a predetermined place and maybe do some post-processing of those artifacts. This will work without changes in your CMakeLists.txt because Conan will set checkbox allowing Conan to modify the default CLion settings and run CMake sequentially instead of in parallel. This is necessary because the Conan cache isn’t concurrent yet in Conan 2. If you’re using the

removing the need to use short_paths in Windows. Note that the cache is still not concurrent, so parallel jobs or tasks should use independent caches. 2.13 New extensions plugins Several extension points libraries, binaries) from the build and source folder to a predetermined place and maybe do some post-processing of those artifacts. This will work without changes in your CMakeLists.txt because Conan will set checkbox allowing Conan to modify the default CLion settings and run CMake sequentially instead of in parallel. This is necessary because the Conan cache isn’t concurrent yet in Conan 2. If you’re using the