Finished

1 year ago

cppcon18

About

Location: Aurora, Colorado, U.S.A Dates: 22nd September 2018 - 30th September 2018 Website: cppcon.org

CppCon is the annual, week-long face-to-face gathering for the entire C++ community. The conference is organized by the C++ community for the community. You will enjoy inspirational talks and a friendly atmosphere designed to help attendees learn from each other, meet interesting people, and generally have a stimulating experience. Taking place this year in Aurora, Colorado, near the Denver airport, and including multiple diverse tracks, the conference will appeal to anyone from C++ novices to experts.

SYCL Sessions At CppCon 2018

Programming Models for GPUs using SYCL

Gordon Brown and Michael Wong (Codeplay Software)

Computer system architecture trends are constantly evolving to provide higher performance and computing power, to support an increasing demand for high-performance computing domains including AI, machine learning, image processing and automotive driving aids. The most recent being the move towards heterogeneity, where a system has more than one kind of processor working together in parallel. These kinds of systems are everywhere, from desktop machines and high-performance computing servers to mobile and embedded devices. SYCL allows users to write standard C++ code which is then executed on a range of heterogeneous architectures including CPUs, GPUs, DSPs, FPGAs and other accelerators. On top of this SYCL also provides a high-level abstraction which allows users to describe their computations as a task graph with data dependencies, while the SYCL runtime performs data dependency analysis and scheduling.

Weekend Class: Parallel Programming with Modern C++: From CPU to GPU

Gordon Brown and Michael Wong (Codeplay Software)

Parallel Programming with Modern C++: from CPU to GPU” is a two-day training course with programming exercises taught by Gordon Brown and Michael Wong. It is offered at the Meydenbauer Conference Center from 9AM to 5PM on Saturday and Sunday, September 29th and 30th

Parallel programming can be used to take advance of multi-core and heterogeneous architectures and can significantly increase the performance of software. It has gained a reputation for being difficult, but is it really? Modern C++ has gone a long way to making parallel programming easier and more accessible; providing both high-level and low-level abstractions. C++11 introduced the C++ memory model and standard threading library which includes threads, futures, promises, mutexes, atomics and more. C++17 takes this further by providing high level parallel algorithms; parallel implementations of many standard algorithms; and much more is expected in C++20. The introduction of the parallel algorithms also opens C++ to supporting non-CPU architectures, such as GPU, FPGAs, APUs and other accelerators.

This course will teach you the fundamentals of parallelism; how to recognise when to use parallelism, how to make the best choices and common parallel patterns such as reduce, map and scan which can be used over and again. It will teach you how to make use of the C++ standard threading library, but it will take this further by teaching you how to extend parallelism to heterogeneous devices, using the SYCL programming model to implement these patterns on a GPU using standard C++.