In the United States, Deloitte LLP and its subsidiaries have 80,000 professionals with a single focus: Serving our clients and helping them solve their toughest problems. Digital reality is the next transformation after PC, web, and mobile. It may dramatically alter the way we interact and use technology and data.
The Khronos Group would like to welcome Contributor Member Shopify. Shopify powers over 800,000 business worldwide as the leading multi-channel commerce platform that helps merchants design, set up, and manage their stores. Today, Shopify joins the Khronos Group to help lead the charge in 3D Commerce - another step in future-proofing their merchants and making commerce better for everyone.
The SYCL Compiler and Runtimes 2019-09 release allow OpenCL offloading to accelerators (GPU/FPGA). Some OpenCLCL/SYCL FPGA extensions are now supported along with support for dumping the SYCL task graph to JSON. Lots of other improvements and fixes are included on the GitHub release page.
LLVM Clang 9.0 has been released and is now available for download. This is the first release to contain experimental support of C++ for OpenCL language mode in Clang. More details can be found in the Clang documentation. This new support will be discussed at the LLVM Developers meeting (October 2019) at the From C++ for OpenCL to C++ for accelerator devices talk by Khronos Member Anastasia Stulova.
A unified programming model offers enterprises and OEMs a cost-effectively way to take advantage of the growing diversity of processor platforms, letting companies share their source code investment across vendors and architectures. Enter oneAPI from Intel, which aims to revolutionize application development through a unified, open development model to simplify programming across processors. Intel built upon C++, and SYCL from The Khronos Group had some really good constructs that they thought provided a very good starting point. Intel extended and improved it to achieve the goals that they wanted to achieve. Most of the DPC++ extensions will eventually be synced upstream into SYCL.
Last week saw the release of Vulkan 1.1.123. The release sees four issues from GitHub addressed and several Khronos internal issues fixed. Two new extensions have also be included: VK_KHR_shader_subgroup_extended_type: enables the Non Uniform Group Operations in SPIR-V to support 8-bit integer, 16-bit integer, 64-bit integer, 16-bit floating-point, and vectors of these types, and VK_GOOGLE_user_type: allows use of the SPV_GOOGLE_user_type extension in SPIR-V shader modules.
Longtime Nouveau developer Karol Herbst has been leading the work on the Nouveau NIR/SPIR-V changes around OpenCL support since joining Red Hat almost two years ago. Arriving in Mesa recently is the SPIR-V support for Nouveau’s NVC0 Gallium3D driver.
In C++, especially in modern C++, function pointers are a legacy feature from the C language but they still exist in some code bases. SYCL does not provide support for function pointers as this is a limitation posed by the design of OpenCL v1.2 which is the basis of the current SYCL v1.2.1 definition. The good news is that we can use modern C++ to implement a solution that can be used with SYCL. Learn how to do this with examples from Codeplay.
Andrew Richards from Codeplay will be presenting “Using Industry-Standard Techniques to Accelerate AI Software” at this years Linley Fall Processor Conference in Santa Clara. You can learn more about this presentation and download a free white paper by Linley Gwennap, Principal Analyst at the Linley Group.
NVIDIA Nsight Systems 2019.5 is now available. This release release offers several improvements to refine the user experience with CLI sessions for simultaneous usage of more commands, improved GUI timeline zooming levels of detail, enhanced Vulkan API coloring, and Linux GPU context switch trace.
Kiriti Nagesh Gowda from the AMD Radeon Technology Group will be speaking at Graphicon 2019 in Bryansk, Russia on September 25th 2019. The talk will be about the MIVisionX toolkit and how to run inference efficiently using OpenVX and OpenVX Extensions.
Founded in 1976, today Acer is one of the world’s top ICT companies and has a presence in over 160 countries. As Acer looks into the future, it is focused on enabling a world where hardware, software and services will fuse with one another to open up new possibilities for consumers and businesses alike.
Marxent is the leader in 3D Asset Management for ecommerce. Marxent’s 3D Cloud is the 3D product visualization platform trusted by Macy’s, John Lewis Partners, Ashley Furniture, and other major retailers in the US and Europe. Hosting hundreds of thousands of products and interacting with millions of users per month, the Marxent 3D Cloud is the proven, enterprise 3D product visualization platform.
Heterogeneous-Compute Interface for Portability (HIP) is a runtime API and a conversion tool to help make CUDA programs more portable. It was originally contributed by AMD to the open source community with the intention to ease the effort of making CUDA applications also work on AMD’s ROCm platform.
While AMD and NVIDIA share the vast majority of the discrete GPU market, it is useful to make this “CUDA portability enhancement route” available to an even wider set of platforms. Since the Khronos OpenCL standard remains the most widely adopted cross-platform heterogeneous programming API/middleware, it is interesting to study whether HIP could be ported on top of it, expanding its scope potentially to all OpenCL supported devices. We in Customized Parallel Computing group, Tampere University, Finland, are happy to announce that to have worked on such a tool, known as HIPCL, for some time and it’s now published and available in Github.
The first release of HIPCL is a proof-of-concept, but is already useful for end-users. It can run most of the CUDA examples in the HIP repository and the list of supported CUDA applications will grow steadily as we add new features.
On September 19 at AutoSens Brussels, Stephane Strahm of Kalray will be joining other attendees to discuss options for addressing the increasingly complex challenges facing automotive vision system engineers. Pushed by developments in markets such as Advanced Driver Assistance Systems (ADAS) and autonomous vehicles, maintaining component interoperability in increasingly complex vehicle subsystems is proving to be a big obstacle.