GPU Tile 1 Tile 0 Xe LinkProject Goals - Offer high-level, standard C++ distributed data structures - Support distributed algorithms - Achieve high performance for both multi-GPU, NUMA, and multi-node reduce(par_unseq, z, 0, std::plus()); }Outline - Background (Ranges, Parallelism, Distributed Data Structures) - Distributed Ranges (Concepts) - Implementation (Algorithms and views) - Complex sparse matrices) - Lessons learnedOutline - Background (Ranges, Parallelism, Distributed Data Structures) - Distributed Ranges (Concepts) - Implementation (Algorithms and views) - Complex

BeyondWe still need to wait for all the player inputs to process the confirm frame…What is a rollback system?Input predictionMispredictionDoing a rollbackRollback Implementation DetailsPhysics vs Graphics game update. This allows to sequence your game frame.A Fixed TickRollback Manager InputsRollbackGame System Architecture Game systems need a function to rollback (revert to a previous state). Typically everywhere Player Character as a gameplay, physics, graphics and audio object…ECS-like architecture System and array of Components (C-struct without functionality, except operators maybe) You want to have

Hlavacs – Combining Co-Routines and Functions into a Job System - CppCon 2021 1 / 39Helmut Hlavacs – Combining Co-Routines and Functions into a Job System - CppCon 2021 2 / 39 About Myself • Professor for Functions into a Job System - CppCon 2021 3 / 39 Creating Game Engines with C++ • Vienna Game Job System + • Graphics API Abstraction Layer + • Vienna Entity Component System + Vienna Type List Library 2.0 https://github.com/hlavacs 20Helmut Hlavacs – Combining Co-Routines and Functions into a Job System - CppCon 2021 4 / 39 The Game Loop auto prev = high_resolution_clock::now(); while( !finished()

program for a supercomputer? Introduce PGAS Model, RDMA Building Remote Pointer Types Building Distributed Data Structures Extending to GPUsThis Talk Background: how do we write a program for a supercomputer supercomputer? Introduce PGAS Model, RDMA Building Remote Pointer Types Building Distributed Data Structures Extending to GPUsThis Talk Background: how do we write a program for a supercomputer? Introduce Introduce PGAS Model, RDMA Building Remote Pointer Types Building Distributed Data Structures Extending to GPUsThis Talk Background: how do we write a program for a supercomputer? Introduce PGAS Model

Zhang tankiistanki tankijong COROUTINE JOB SYSTEM WITHOUT STANDARD LIBRARY source code of the system: https://github.com/tankiJong/cpp-coroutine-job-system Hi Everyone, Tanki here. Thanks for coming resources: https://gist.github.com/MattPD/9b55db49537a90545a90447392ad3aeb Before we dive into the system, I want to take 10 mins to have a quick recap about C++ coroutine and share some gotcha moments pretty overwhelmed by all different terms, not to mention to put them up together to form a knowledge system. I hope the following information can be helpful and I attached some links in the slides, or pointers

from Columbia University. Title : Behavior-driven Tests for Microservices-based Algo Trading System Summary : Introduction : This poster will introduce a test framework we use at Bloomberg to to enable behavior-based tests in natural language style for a microservices-based algo trading system that our engineering team is responsible for. Relevance : For our electronic trading business Although microservice components can easily be unit tested, it is often non-trivial to automate the system-level tests with external dependencies. Controlling external dependencies are especially important

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 308 25 Multi-processing and Distributed Computing 310 25.1 Code Availability and Loading Packages . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 363 28 Handling Operating System Variation 366 29 Environment Variables 367 29.1 File locations . . . . . . . . . . . . . . . . formatting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 373CONTENTS vi 29.7 System and Package Image Building . . . . . . . . . . . . . . . . . . . . . . . . . . 374 29.8 Debugging

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 308 25 Multi-processing and Distributed Computing 310 25.1 Code Availability and Loading Packages . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 363 28 Handling Operating System Variation 366 29 Environment Variables 367 29.1 File locations . . . . . . . . . . . . . . . . formatting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 373CONTENTS vi 29.7 System and Package Image Building . . . . . . . . . . . . . . . . . . . . . . . . . . 374 29.8 Debugging

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 327 26 Multi-processing and Distributed Computing 329 26.1 Code Availability and Loading Packages . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 385 29 Handling Operating System Variation 388CONTENTS vi 30 Environment Variables 389 30.1 File locations . . . . . . . . . . REPL formatting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 396 30.7 System and Package Image Building . . . . . . . . . . . . . . . . . . . . . . . . . . 397 30.8 Debugging

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 327 26 Multi-processing and Distributed Computing 329 26.1 Code Availability and Loading Packages . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 385 29 Handling Operating System Variation 388CONTENTS vi 30 Environment Variables 389 30.1 File locations . . . . . . . . . . REPL formatting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 396 30.7 System and Package Image Building . . . . . . . . . . . . . . . . . . . . . . . . . . 397 30.8 Debugging