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.