Heterogeneous Programming using ComputeCPP, C++17 Parallel STL and C++ Concurrency | CEE-SECR 2016 Heterogeneous Programming using ComputeCPP, C++17 Parallel STL and C++ Concurrency – CEE-SECR 2016
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Master-classes

Heterogeneous Programming using ComputeCPP, C++17 Parallel STL and C++ Concurrency

Michael Wong

October 30, 2016
8 hours

In English with translation to Russian
Requires separate registration

The Khronos™ Group maintains the OpenCL™ and SYCL™ standards, both designed to offer dispatch using C and C++ to heterogeneous devices such as GPUs, integrated CPUs, DSPs and even FPGAs. The C++ Standard is also building towards similar support starting with the C++17 Parallel and Concurrency Technical Specifications, but currently is restricted to CPUs. With the help of early design experience from SYCL, and other heterogeneous computing models, it will enable a single high-level performance-portable programming standard for programming autonomous vehicles, computer vision, and neural networks.

SYCL is already able to disptach to heterogeneous devices and it implements C++17 ParallelSTL augmenting it with ability to dispatch to GPUs in addition to CPUs. This workshop will demonstrate how to write parallel SYCL code and how to use the Khronos Group’s experimental Parallel STL implementation. The course outline is as follows

  • start with a basic Hello World-style program that shows how to submit queues in a single task and stream-like object, comparing CPU, SYCL and OpenCL version
  • demonstrate how to access data across host and GPUs using buffers and accessors, the importance of life-time, and basic parallel constructs
  • use advanced techniques such as aussian blur to handle images, that can lead to computer vision useful for pedestrian detection
  • demonstrate C++17 parallel algorithms using SYCL’s parallelSTL implementation that can dispatch to not just CPU, but heterogeneous devices

Along with the hands-on workshop, we will also deliver lectures that describe SYCL and OpenCL as well as C++ Parallelism and Concurrency Technical Specifications, including C++17’s Parallel STL, C++11 async, futures, atomics, and emerging specifications on continuation-style programming, latches, barriers, atomic shared_ptr, as well as lock-free programming toolkits.

Attendees are expected to have programming experience with C++ and a laptop. The suitable software will be provided on USB-sticks. This course is suitable for beginners, but is focused on intermediate to advanced parallel programming using C++.

About master-class instructors

Michael Wong

Michael Wong

VP Research and Development, Codeplay Software


Michael Wong is the Vice President of Research and Development at Codeplay Software, Director and VP of ISOCPP.org, a senior member of the C++ Standards Committee with 15 years of experience and Vice-Chair of Programming Languages for Canada’s Standard Council. He is the Head of Delegation for Canada to the C++ Standard Committee and the past CEO of OpenMP. Previously Michael was the Senior Technical Strategy Architect for IBM compilers.

Michael chairs the WG21 SG5 Transactional Memory and SG14 Games Development/Low Latency/Financials, and is the co-author of a number of C++/OpenMP/Transactional Memory features including generalized attributes, user-defined literals, inheriting constructors, weakly ordered memory models, and explicit conversion operators. He has published numerous research papers and is the author of a book on C++11, and he is the current Editor for the Concurrency TS and the Transactional Memory TS.

Michael has been invited to speak and deliver keynotes at many conferences, universities, companies and research institutions including ACCU, C++Now, Meeting C++, ADC++, CASCON, Bloomberg, Activision/Blizzard, and CERN.

Duncan McBain

Duncan McBain

Developer Relations Manager, Codeplay Software

Duncan is a software engineer at Codeplay. He started out on the EU-funded LPGPU project, looking at ways of improving performance on and reducing power usage of GPU devices. Since then he has worked on client projects and recently was working on Codeplay’s implementation of SYCL, ComputeCPP. Most recently, he has been providing support to external developers who use ComputeCPP.

Duncan was first exposed to heterogeneous programming in the High Performance Computing course at the University of Edinburgh. For his dissertation he used the CUDA API to speed up FFT calculations in an open-source primality-testing code. This experience was enough to instigate a fascination with heterogeneous devices and the performance possibilities that they bring.


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