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.
bgfx popular open source cross-platform rendering library adds Vulkan renderer backend. Vulkan renderer backend will be bgfx’ default renderer on Linux, and it can be used on all supported platforms including MacOS via MoltenVK emulation.
Hardware accelerators are power efficient implementations of challenging algorithms in heterogeneous computing platforms which are used to make key tasks in applications such as video codecs or machine vision pipelines faster, more power efficient, and less chip area consuming. Fixed function hardware accelerators are the latest class of devices Portable Computing Language (<a href=“http://portablecl.org”>POCL</a>) adds to its diverse palette of supported device types in the same OpenCL context.
Diligent Engine is a modern cross-platform low-level graphics library and rendering framework. In a recent update, Diligent Engine enabled support of GLTF 2.0 format. It also implemented physically-based renderer with image-based lighting and released cross-platform GLTF viewer as example application.
Flax Engine moves towards cross-platform gaming. Adding Vulkan rendering backend implementation into the engine resulting in greater efficiency, performance, and stability. We see a huge potential of Vulkan API as it opens ways to new areas for Flax to expand including Linux and Android support.
In a recent article of Science Advances, we introduced a WebGL library Abubu.js that makes easier to program and create high-performance simulation of cardiac dynamics and other large-scale systems like fluid flow and crystal growth. Making these kind of simulations and studies accessible to virtually anyone with a modest computer. For cardiac dynamics, this approach will allow not only scientists and students but also physicians to use physiologically accurate modeling and simulation tools that are interactive in real time, thereby making diagnostics, research, and education available to a broader audience and pushing the boundaries of cardiac science.
Codeplay Software has announced the availability of this fully supported edition of their popular SYCL implementation providing advanced features and premium technical support to developers seeking to bring advanced vision and AI products to the market. The first releases will support Intel GPUs and Renesas R-Car products, with other platforms becoming available soon.
ncnn is a widely-used opensource neural network inference framework optimized for mobile platforms. It supports commonly used CNN models such as resnet, mobilenet, ssd, yolo etc. , converted from caffe, mxnet, onnx etc. The ncnn community used to focus on high performance computing optimization on mobile CPU using arm neon technology. The latest ncnn version added gpu-acceleration via Vulkan compute, which brings a cross-platform and vendor-independent neural network inference solution from desktop to mobile. The ncnn Vulkan acceleration runs natively on Windows, Linux, Android, and MacOS, iOS via MoltenVK project.