Opencl tagged stories

With an increasing number of OpenCL run-times supporting ingestion of SPIR-V, OpenCL developers may wish to use offline compilation to precompile SPIR-V kernels that can be used portably across multiple OpenCL implementations. Consistently using the same front-end compiler can enhance cross-vendor deployment consistency, while reducing overall compile times and eliminating the need to ship OpenCL C source code. Kernel development may also be more

The Khronos® OpenCL™ working group recently created a new Tooling Subgroup with the aim of improving the tools ecosystem for this widely-used open standard for heterogeneous computation—in particular, boosting the development of tooling components that can be shared by multiple vendors. Subgroup members have been meeting regularly to coordinate the overall direction for OpenCL tools, with an emphasis on strengthening the development of tools in open source, particularly by encouraging collaboration between the OpenCL and LLVM communities.

In April, Khronos introduced the Safety Critical Advisory Forum was created in response to developers’ growing concerns and demands of functional safety standards on hardware and software. The advice and support that the forum provides to Khronos Working Groups directly contributes to the creation of SC APIs. Members and non-members can contribute in the forum, this post outlines the benefits of participation.

On May 16, OpenCL 2.2 was released by Khronos Group. The most important part of the new OpenCL version is support for OpenCL C++ kernel language, which is defined as a static subset of the C++14 standard. OpenCL C++ introduces long-awaited features such as classes, templates, lambda expressions, function and operator overloads, and several other constructs which increase parallel programming productivity through generic programming.

Don’t miss this year’s OpenVX Workshop at Embedded Vision Summit. Khronos will present a day-long hands-on workshop all about OpenVX cross-platform neural network acceleration API for embedded vision applications. We’ve developed a new curriculum so even if you attended in past years, this is a do-not-miss, jam-packed tutorial with new information on computer vision algorithms for feature tracking and neural networks mapped to the graph API. We’ll be doing a hands-on practice session that gives participants a chance to solve real computer vision problems using OpenVX with the folks who created the API. We’ll also be talking about the OpenVX roadmap and what’s to come.