OpenCL related stories

NVIDIA GPU Technology Conference (GTC2017) to offer great sessions on Khronos Technology

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The GPU Technology Conference (GTC2017) will be running from May 8-11 this year in San Jose Convention Center. This year will see many sessions related to Khronos Technology including OpenCL, OpenGL, OpenVX, Vulkan and WebGL. Check a list of Khronos technology only sessions on the Khronos site, or visit the NVIDIA GTC site to see all sessions.

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ARM announces Computer Vision and Machine Learning library with OpenCL

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ARM has open-sourced a new compute library with GPU support via OpenCL as well as CPU support with NEON usage. The ARM Compute Library works on both Linux and Android. Source: Phoronix.

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IWOCL early bird pricing now available

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Registration to IWOCL is now open. The 5th International Workshop on OpenCL will take place in Toronto, Canada on May 16-18, 2017. Act quickly to get Early Bird pricing, available until April 14th.

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KDevelop offers OpenCL language support

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KDevelop, a cross-platform IDE for C, C++, Python, JavaScript and PHP, is now offering OpenCL language support. KDevelop 5.1 and on has been able to parse code written in OpenCL the Clang-based language support backend.

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Machine learning-ready FPGAs from the edge to the cloud with OpenVX and OpenCL

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Xilinx, Inc announced expansion into a wide range of vision guided machine learning applications with the Xilinx reVISION stack. Developers with limited hardware expertise can use a C/C++/OpenCL development flow with industry-standard frameworks and libraries like Caffe and OpenCV to develop embedded vision applications on a single Zynq SoC or MPSoC. For application level development, Xilinx supports industry-standard frameworks including Caffe for machine learning and OpenVX for computer vision.

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Imagination’s Furian GPU a massive step up in performance with OpenCL 2.0, Vulkan 1.0 and OpenVX 1.1

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Furian is designed to address the increasing compute requirements across multiple applications and market segments with efficient use of compute APIs including OpenCL 2.0, Vulkan 1.0 and OpenVX 1.1*. Furian adds a bi-directional GPU/CPU coherent interface for efficient sharing of data; and a transition to user mode queues from kernel mode queues which reduces latency and CPU utilization for compute operations. Based on a published Khronos specification, GPUs based on the PowerVR Furian architecture are expected to pass the Khronos Conformance Testing Process. Current conformance status can be found at www.khronos.org/conformance.

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OpenCL-based Nengo Simulator

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This project is an OpenCL-based simulator for brain models built using Nengo. It can be orders of magnitude faster than the reference simulator in nengo for large models. Nengo is a Python library for creating and simulating large-scale brain models.

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NVIDIA 378.66 drivers for Windows offer OpenCL 2.0 evaluation support

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NVIDIA graphics driver for Windows version 378.66 is now offering some OpenCL 2.0 support. From the release notes: "New features in OpenCL 2.0 are available in the driver for evaluation purposes only." Some known issues include: The current implementation is limited to 64-bit platforms only; OpenCL 2.0 allows kernels to be enqueued with global_work_size larger than the compute capability of the NVIDIA GPU. The current implementation supports only combinations of global_work_size and local_work_size that are within the compute capability of the NVIDIA GPU; For executing kernels (whether from the host or the device), OpenCL 2.0 supports non-uniform ND-ranges where global_work_size does not need to be divisible by the local_work_size. This capability is not yet supported in the NVIDIA driver, and therefore not supported for device side kernel enqueues.

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Intel FPGAs Break Record for Deep Learning Facial Recognition using OpenCL SDK

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Today Intel announced record results on a new benchmark in deep learning and convolutional neural networks (CNN). The test took place in Nanjing City, China, where ZTE’s engineers used Intel’s midrange Arria 10 FPGA for a cloud inferencing application using a CNN algorithm. The benchmark was achieved on a server holding 4S Intel Xeon E5-2670v3 processors running at 2.30GHz, 128GB DDR4; Intel PSG Arria 10 FPGA Development Kit with one 10AGX115 FPGA, 4GB DDR4 SODIMM, Intel Quartus Prime and OpenCL SDK v16.1. Besides the impressive increase in performance, the team at the ZTE Wireless Institute sped design time with the use of the OpenCL programming language.

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Submit your OpenCL abstracts and papers for IWOCL 2017 in Toronto

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Only 10 days left to get your OpenCL abstracts and papers in for IWOCL 2017 in Toronto.

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