Stream Computing is offering OpenCL training in Amsterdam in January 2017. For those wanting to learn solid GPU programming. This is a public training with trainees from various companies – get in contact if you want to learn more about our in-company trainings. For pre-requisites and pricing, please see the Stream Computing website.
Using OpenCL, programmers can utilize FPGAs with C, or other familiar high- level programming languages, instead of hardware-specific language. At SC16, one of the major issues for discussion is optimizing OpenCL kernels for high-performance computing.
Today sees the emergence of ROCm (Radeon Open Compute Platform) 1.3, which brings the official release of the LLVM native compiler and support for AMD’s current Polaris family of 14nm GPUs (Radeon RX 480, RX 470, RX 460). Also hopping aboard is support for OpenCL 1.2+. More specifically, ROCm 1.3 support the OpenCL 1.2 runtime along with the OpenCL 2.0 kernel language.
Nimbix announced the availability of the Xilinx SDAccel development environment for on-demand development, testing, and deployment of FPGA-accelerated workflows in the Nimbix Cloud, powered by JARVICE. The SDAccel development environment combines the industry's first architecturally optimizing compiler supporting any combination of OpenCL, C, and C++ kernels, along with libraries, development boards and industry standard development and run‐time experience for FPGAs.
Huawei Consumer Business Group event saw the unveiling of the HUAWEI Mate 9 using the Kirin 960 chipset. The Kirin 960 features an ARM Cortex-A73/A53 Octa-core CPU and Mali G71 Octa-core GPU. The GPU boasts a 180 percent performance uplift and a 40 percent improvement in energy efficiency compared to its predecessor. The Kirin 960 also takes full advantage of the pioneering Vulkan graphics standard on Android 7.0, increasing graphics performance by up to 400 percent.
Qualcomm Incorporated announced that its subsidiary, Qualcomm Technologies, Inc., has introduced three new next-generation Qualcomm Snapdragon processors: the Snapdragon 625, 435 and 425. The 625 supports PC-class graphics with the Qualcomm Adreno 506 GPU, which is designed to support the Vulkan API*. Adreno 505 and Adreno 506 are being designed to support the upcoming final version of Vulkan. Current specification status can be found at www.khronos.org/vulkan.
Graphics researchers at Samsung Electronics UK have teamed up with mobile graphics specialists Codeplay, Think Silicon and TU Berlin to develop a tool for enabling smartphone batteries to last longer while running advanced video games and using the camera. "Low-power GPU2" (LPGPU2) is a EU-funded research project into low powered graphics devices. It is the work of a specially formed consortium of three companies and one university, all from across the EU, who are collaborating to deliver advances in tools and applications for energy efficient use of mobile GPUs.
For developers new to graphics optimization this new series of blog posts from ARM is all about giving content developers the essential knowledge they need to successfully optimize for Mali GPUs. Over the course of the series, Peter Harris explores the fundamental macro-scale architectural structures and behaviors developers have to worry about, how this translates into possible problems which can be triggered by content, and finally how to spot them in Streamline.
Basemark announced a new product called Basemark GPU Vulkan. This benchmarking software enables the industry to objectively and reliably quantify and compare graphics and computing performance of next generation mobile and desktop processors compatible with the new generation Vulkan API from the Khronos Group. Basemark GPU Vulkan is developed in close cooperation with key player semiconductor companies, such as AMD, Imagination Technologies, Intel, NVIDIA, Qualcomm and Renesas within Basemark’s benchmark development program.
ARM announced a new GPU from the same family as Mali-400 that uses only half as much power. The new GPU, the Mali-470, is targeted at next-generation wearables and IoT devices that need low-cost and low-power chips. The new Mali-470 comes with support for the ubiquitous OpenGL ES 2.0 graphics API. According to ARM, it brings a strong balance between pixel control and energy efficiency, which makes it well-suited for user interfaces. Users aren't likely to play 3D games on their smartwatches any time soon, so OpenGL ES 3.0 and beyond shouldn't be necessary. (By the time it is, the more efficient Vulkan should be the de facto graphics API.)
Qualcomm Incorporated announced two new Qualcomm Snapdragon processors. The new chipsets, the Snapdragon 430 and the Snapdragon 617, offer advances in both multimedia and connectivity for mid-range mobile devices. The Snapdragon 430 uses the powerful new Qualcomm Adreno 505 GPU with support for Open GL ES 3.1 and OpenCL 2.0.
In a white paper released during a semiconductor design conference last week in Silicon Valley, researchers from the University of Wisconsin-Madison outlined the architecture of the open source GPU dubbed MIAOW, or Many-core Integrated Accelerator of Wisconsin. The prototype was essentially designed to demonstrate an open source GPGPU compatible with OpenCL. The researchers said their goal was to emulate a full system, not to compete with commercial designs.
The PowerVR Imaging Framework for Android comprises a set of extensions to the OpenCL and EGL Application Programming Interfaces (APIs) that enable efficient interoperability of software running on PowerVR GPUs with other components such as a CPU, ISP and VDE. These extensions enable the construction of shared memory allocations and software pipelines across multiple hardware components with no redundant memory copies (termed zero-copy). The framework is integrated at the library layer of the Android software stack, enabling efficient interoperability between APIs such as OpenCL, OpenGL ES and emerging APIs such as OpenVX.
This Imagination Technologies article and a follow-up to be published next month introduce OpenCL programming for the PowerVR Rogue architecture. Starting with an overview of OpenCL programming fundamentals using a basic program, followed by an explanation of OpenCL execution on Rogue GPUs. This provides the background to understand the programming guidelines for the Rogue architecture which are illustrated by using a case study of an image filtering program.