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A parallel computing platform and application programming interface model,it enables developers to speed up compute-intensive applications by harnessing the power of GPUs for the parallelizable part of the computation.
3,657개의 회사가 CUDA를 사용하는 데이터가 있습니다. 이 정리된 목록은 다운로드 가능하며, 산업 분류, 조직 규모, 지리적 위치, 자금 조달 라운드, 수익 수치 등을 포함한 중요한 회사 정보로 풍부하게 구성되어 있습니다.
회사 | 나라 | 산업 | 직원 | 수익 |
---|---|---|---|---|
NVIDIA | 미국 | Computer Hardware Manufacturing | 32K | $27B |
Oski Technology | 미국 | Computer Hardware Manufacturing | 27K | $27B |
Northrop Grumman | 미국 | Defense And Space Manufacturing | 88K | $35B |
Swinburne University of Technology | 오스트레일리아 | Higher Education | 6.2K | |
DeepSight Technology | 미국 | Medical Equipment Manufacturing | 33 | |
Lockheed Martin | 미국 | Defense And Space Manufacturing | 111K | $66B |
Valeo | 프랑스 | Motor Vehicle Parts Manufacturing | 115K | $22B |
Livario GmbH | 독일 | Retail Apparel And Fashion | 22 | |
Sinopec Tech Houston | 미국 | Oil And Gas | 41 | |
Evertz Microsystems Limited | 캐나다 | Manufacturing | 1.2K | $332M |
Zendar | 미국 | Software Development | 40 | $2.7M |
CentML | 캐나다 | Software Development | 5K | $11M |
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기술 사용 통계 및 시장 점유율
이 데이터를 지리, 산업, 회사 규모, 수익, 기술 사용, 직무 및 기타 조건으로 필터링하여 필요에 맞게 맞춤화할 수 있습니다. 데이터를 Excel 또는 CSV 형식으로 다운로드할 수 있습니다.
이 데이터를 위한 알림을 받을 수 있습니다. 관심 있는 기술을 선택하면, 그 기술을 사용하는 새로운 회사가 있을 때 받은 편지함에서 알림을 받게 됩니다.
데이터를 Excel 파일로 내보낼 수 있으며, 이를 CRM에 가져올 수 있습니다. 또한 데이터를 API로 내보낼 수도 있습니다.
CUDA는 51 국가에서 사용되고 있습니다.
CUDA 대안이 76가지 있습니다
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자주 묻는 질문
우리의 데이터는 수백만 개의 회사에서 수집된 채용 공고에서 출처를 얻습니다. 우리는 이러한 공고를 회사 웹사이트, 구인 게시판, 기타 채용 플랫폼에서 모니터링합니다. 채용 공고 분석은 회사들이 사용하는 기술과 내부 도구의 사용을 이해하는 신뢰할 수 있는 방법을 제공합니다.
우리는 최신 정보를 제공하기 위해 데이터를 매일 갱신합니다. 이 빈번한 업데이트 과정은 우리의 인사이트와 지능이 업계 내 최신 동향과 발전을 반영하도록 보장합니다.
CUDA, which stands for Compute Unified Device Architecture, is a parallel computing platform and programming model developed by NVIDIA. It allows software developers to harness the power of NVIDIA GPUs for general-purpose processing, particularly in tasks requiring high computational power. By offloading intensive parallel computation tasks from the CPU to the GPU, CUDA enables significant acceleration of applications across various domains, including scientific simulations, deep learning, image processing, and more.
CUDA falls under the category of Machine Learning Tools due to its crucial role in accelerating machine learning algorithms using GPU parallelism. Machine learning models often involve complex computations that can benefit greatly from the parallel processing capabilities of GPUs. CUDA provides the infrastructure and tools necessary to exploit GPU acceleration for training and inference tasks in machine learning, making it a popular choice among data scientists and machine learning engineers.
CUDA was founded by NVIDIA Corporation in 2006 with the primary goal of enabling developers to leverage the power of GPU computing for general-purpose applications. The initial motivation behind CUDA was to address the increasing demand for high-performance computing solutions that could handle complex parallel workloads efficiently. As a pioneer in GPU technology, NVIDIA saw an opportunity to revolutionize parallel computing by providing a platform that could unlock the massive parallel processing capabilities of GPUs for a broader range of applications.
Currently, CUDA holds a dominant position in the market for GPU computing platforms, with a significant market share within the Machine Learning Tools category. As the demand for accelerated computing continues to rise, fueled by the growth of artificial intelligence and big data analytics, CUDA is poised to maintain its market dominance and even expand its reach further. The forecast suggests that CUDA is likely to see continuous growth in the future, driven by the increasing adoption of GPU acceleration in diverse computing applications.
CUDA, a parallel computing platform and application programming interface created by NVIDIA, is widely utilized by companies in the machine learning field for its exceptional performance and scalability. By harnessing the power of GPU-accelerated computing, CUDA allows organizations to expedite complex data processing tasks and train machine learning models with unparalleled efficiency.
CUDA significantly accelerates computing tasks by offloading intensive calculations to the GPU. This faster processing speed enables companies to reduce their model training times drastically, leading to quicker insights and improved productivity compared to traditional CPU-based systems.
One of CUDA's key advantages is its ability to handle massive parallel processing, allowing for simultaneous execution of multiple operations. This enhanced parallelism not only boosts overall system performance but also enables companies to tackle intricate machine learning algorithms with ease, surpassing the capabilities of other parallel computing technologies.
CUDA optimizes resource utilization by efficiently distributing workloads between the CPU and GPU. This balanced approach results in better overall system performance and cost-effectiveness, making it a preferred choice for companies looking to maximize their computing resources effectively.
Companies Using CUDA:
CUDA, developed by NVIDIA, is a parallel computing platform and application programming interface model that enables developers to use NVIDIA GPUs for general-purpose processing, including accelerating tasks related to machine learning and artificial intelligence. Several prominent companies leverage CUDA to enhance the performance of their applications and deliver cutting-edge solutions in various domains. Here are some real-world examples of companies that have successfully integrated CUDA into their operations:
NVIDIA: NVIDIA, the pioneer of CUDA technology, extensively uses it for various applications, including deep learning, image processing, and scientific simulations. NVIDIA started utilizing CUDA in 2007 and has since optimized its GPUs to support a wide range of machine learning tasks.
Adobe Systems: Adobe Systems, a leading software company, incorporates CUDA in its Adobe Creative Cloud suite for accelerating graphics processing tasks. By leveraging CUDA's parallel computing capabilities, Adobe has significantly improved the performance of applications like Adobe Photoshop for tasks such as image editing and rendering. Adobe adopted CUDA technology in 2013.
Netflix: Netflix, the renowned streaming service provider, utilizes CUDA to enhance its recommendation algorithms and video encoding processes. By harnessing CUDA's computing power, Netflix can analyze massive amounts of viewer data efficiently to personalize recommendations and optimize video streaming quality. Netflix began integrating CUDA technology into its operations in 2015.
These case studies highlight how companies like NVIDIA, Adobe Systems, and Netflix have harnessed the power of CUDA to drive innovation, improve performance, and deliver a superior user experience in the realm of machine learning tools. By leveraging CUDA's parallel processing capabilities, these companies have successfully enhanced their applications and services, showcasing the versatility and effectiveness of this technology in transforming business operations.
TheirStack.com를 방문하여 CUDA를 사용하는 회사의 최신 목록에 접근할 수 있습니다. 우리의 플랫폼은 다양한 기술과 내부 도구를 사용하는 회사들의 포괄적인 데이터베이스를 제공합니다.
현재 우리는 CUDA을 사용하는 3,657 개 회사에 대한 데이터를 보유하고 있습니다.
CUDA은(는) "Computer Hardware Manufacturing", "Computer Hardware Manufacturing", "Defense And Space Manufacturing", "Higher Education", "Medical Equipment Manufacturing", "Defense And Space Manufacturing", "Motor Vehicle Parts Manufacturing", "Retail Apparel And Fashion", "Oil And Gas", "Manufacturing"을(를) 포함한 다양한 산업 분야의 조직에 의해 사용됩니다. CUDA을(를) 사용하는 모든 산업의 포괄적인 목록은 TheirStack.com을 방문해 주세요.
CUDA을 사용하는 회사 중에는 NVIDIA, Oski Technology, Northrop Grumman, Swinburne University of Technology, DeepSight Technology, Lockheed Martin, Valeo, Livario GmbH, Sinopec Tech Houston, Evertz Microsystems Limited 등이 있습니다. CUDA을 사용하는 3,657개의 회사 목록은 TheirStack.com에서 확인할 수 있습니다.
우리 데이터에 따르면, CUDA는 미국 (1,477 companies), 영국 (230 companies), 독일 (166 companies), 프랑스 (120 companies), 캐나다 (117 companies), 스페인 (68 companies), 인도 (65 companies), 네덜란드 (43 companies), 싱가포르 (30 companies), 오스트레일리아 (29 companies)에서 가장 인기가 많습니다. 그러나, 그것은 전 세계의 기업들에 의해 사용되고 있습니다.
TheirStack.com에서 CUDA을 사용하고 있는 회사를 검색하여 찾을 수 있습니다. 우리는 수백만 개의 회사에서 올라온 채용 공고를 추적하여 그들이 사용하는 기술과 내부 도구를 발견합니다.