Companies that use OpenCL
It is the open, royalty-free standard for cross-platform, parallel programming of diverse processors found in personal computers, servers, mobile devices and embedded platforms. It greatly improves the speed and responsiveness of a wide spectrum of applications in numerous market categories including gaming and entertainment titles, scientific and medical software, professional creative tools, vision processing, and neural network training and inferencing.
2,284
companies
List of companies using OpenCL
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--header "Accept: application/json" \
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-d "{
\"company_technology_slug_or\": [
\"opencl\"
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OpenCL
Employees52kRevenue$23BSemiconductor ManufacturingOpenCLHigh confidence
Employees1.1kRevenue$110MSemiconductor ManufacturingOpenCLHigh confidence- Employees109Software DevelopmentOpenCLHigh confidence
- Employees4Revenue$35MIT Services and IT ConsultingOpenCLHigh confidence
Employees53kRevenue$27BComputer Hardware ManufacturingOpenCLMedium confidence
Employees57kRevenue$44BTelecommunicationsOpenCLMedium confidence
Employees293kComputer Hardware ManufacturingOpenCLMedium confidence
Employees150kRevenue$79BSemiconductor ManufacturingOpenCLMedium confidence
Employees16kIT Services and IT ConsultingOpenCLMedium confidence
Employees166kSoftware DevelopmentOpenCLMedium confidence
We have data on 2,284 companies and users that use OpenCL. Our OpenCL users and customers list is available for download and comes enriched with vital company specifics, including industry classification, organizational size, geographical location, funding rounds, and revenue figures, among others.
Technology Usage Statistics and Market Share
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Frequently asked questions
Our data is sourced from job postings collected from millions of companies. We monitor these postings on company websites, job boards, and other recruitment platforms. Analyzing job postings provides a reliable method to understand the technologies companies are employing, including their use of internal tools.
We refresh our data daily to ensure you are accessing the most current information available. This frequent updating process guarantees that our insights and intelligence reflect the latest developments and trends within the industry.
OpenCL, which stands for Open Computing Language, is a framework for programming parallel computing across CPUs, GPUs, and other processors. It allows developers to write code that can be executed across different devices, taking advantage of the parallel processing power available in modern hardware architectures. OpenCL is particularly useful for tasks that can be parallelized, such as image and video processing, scientific simulations, and machine learning algorithms.
The category of OpenCL falls under "Language Extensions" in the technology landscape. Language extensions provide additional functionality or capabilities to existing programming languages, allowing developers to work more efficiently or target specific hardware features. In the case of OpenCL, it extends languages like C and C++ to support parallel computing across heterogeneous devices, making it a powerful tool for high-performance computing.
OpenCL was founded by the Khronos Group, a consortium of technology companies aiming to create open standards for parallel computing. It was first released in 2009 as an open-source standard, with the goal of providing a vendor-agnostic framework for parallel programming. The motivation behind OpenCL was to enable developers to leverage the full potential of multi-core CPUs, GPUs, and other accelerators without being tied to a specific hardware vendor.
As for the current market share of OpenCL within the Language Extensions category, it holds a significant position due to its wide adoption in industries that require high-performance computing. While newer technologies like CUDA have gained traction in specific domains, OpenCL continues to be a popular choice for its cross-platform compatibility and support for diverse hardware architectures. With the increasing demand for parallel computing solutions, OpenCL is likely to maintain its market share and even grow as more applications require efficient utilization of computing resources.