Hire CUDA developers

Hire CUDA developers

CUDA is a programming model and a parallel computing platform that is developed with the purpose of general computing on graphical processing units. The graphical computing units (GPUs) have tremendous power, and CUDA harnesses this power to increase the speed of computing applications. When such harnessed power is used for building applications, the intensive component of the applications runs on thousands of GPU cores in parallel with the CPU. The sequential component of such applications runs on the CPU.

The CPU for a GPU accelerated application must be optimized for single-threaded performance. CUDA developers use programming languages such as C, C++, Fortran, Python and MATLAB for developing CUDA based applications. NVIDIA, the original developer of CUDA, provides a toolkit that includes all the things needed to develop a GPU accelerated application. This toolkit, the CUDA Toolkit, contains development tools, debugging and optimization tools, libraries, and a compiler, all of which are GPU accelerated. CUDA can be used in developing applications for embedded systems, workstations, data centres and in the cloud. CUDA can be used across all the GPU accelerated applications as it allows the users to scale their applications across GPU configurations and also deploy them.

Learn more about CUDA

CUDA has been developed by Nvidia. The initial version of CUDA was released on 23 June 2007. CUDA is supported by Windows and Linux. The latest version of CUDA was released on 20 May 2021. It is operated on supported GPU platforms. CUDA is a type of GPGPU. CUDA is the world's first solution that can be used for general computing on all GPUs. It is a very user-friendly solution. On initial buying of the CUDA Toolkit, you (the user) are provided with sample codes, user manuals, API references, programming guides and a few other documents that will make you comfortable with CUDA and help you begin your journey as a CUDA developer.

CUDA has applications in numerous fields. Some of them are computational science, numerical analytics, image processing, deep learning, computational chemistry, machine learning, data science, weather and climate, computational fluid dynamics, medical imaging, environmental science, and bioinformatics.

Important features of CUDA

• CUDA compiler - CUDA has its own compiler. The latest version of CUDA introduced additions such as cu++flt, NVRTC shared library versioning scheme, CUDA C++ language and CUDA device linker. With cu++flt, the user can decode mangled functions with ease. The CUDA device linker can dump the call graph for the device code. This facilitates performance analysis and tuning.
• C++ support library - CUDA has a standard C++ library called the libcu++. This library can be used to implement the code in C++ language between the CPU and GPU. libcu++ functions better with certain hardware. It gives an enhanced performance with some keys. This library is available to download for anyone on GitHub.
• Stream-ordered memory allocator - CUDA recently was updated with a new feature of stream-ordered memory allocation. This feature enables the applications using CUDA to order their memory allocation and memory deallocation. The most exciting thing about this feature is that the user can divert and share memory pools through various components within an application.
• CUDA Graphs - CUDA Graphs are a series of operations. They can be connected by dependencies that are separate from their execution. CUDA graphs have exciting features such as Stream capture composability, User objects and Debug API. Graphs do not need constant defining. They can be defined once, and they are good to go for the rest of their operation. A single defined graph can be used for multiple launches.

Roles, responsibilities and skills of a CUDA developer

• To have a strong knowledge of programming languages such as C, C++, Python
• To effectively work with multiple databases such as MS-SQL, MySQL, MS Access
• To coordinate with analysts and designers for testing of new software programs and applications
• To implement procedures for planning, requirements gathering and designing software applications
• To execute procedures for quality assurance
• To provide technical assistance for designing, development and troubleshooting
• To develop unit testing services for failure models
• To prepare software development strategies, structure and architecture for new applications
• To conduct a detailed review of business requirements
• To conduct research and development of technologies for integration into applications

Skills Required

• To develop clean and robust program code
• To maintain technical documentation and related resources
• To ensure timely and high-quality software releases
• To triage automated infrastructure failures
• To develop and expand test coverage
• To identify the right matrix of software and hardware to ensure a high-quality product
• To closely partner with DevOps and Engineering
• To meet aggressive goals and high-quality standards
• To have proven abilities in test case writing and script development
• To have a strong aptitude for learning new technologies
• To be familiar with advanced concepts of computer architecture and data structures
• To follow standard programming practices

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Skuad can help you hire certified and experienced CUDA Developers from all over the world based on your hiring requirements, be it freelance, full-time, or contract.

Salary Structure of a CUDA developer

On average, a CUDA developer is offered US $119,965 per year. The salary of a CUDA developer depends on your experience. The more experience you have, the more salary you are offered. It also depends on the location of work. Some countries which are economically strong offer exciting packages while others not so much. You need to be smart while selecting your location of work as a CUDA Developer. In India, a CUDA developer has a salary structure between US $18,831.76 (₹ 1,400,000) to US $41,698.91 (₹ 3,100,000). On average, a CUDA developer in India gets paid US $29,592.77 (₹ 2,200,000) per year. Beginners in the field are offered way less due to the lack of real-world experience. A CUDA developer in the United Kingdom earns, on average, US $76,179.12 (£ 55,000) every year. The United Kingdom offers an average annual salary in the range of US $64,059.72 (£ 46,250) to US $83,104.50 (£ 60,000).

Freelancing and Contractual basis work

Talented and skilled individuals often find it difficult to find a full-time job in their niche. Most companies are small scale and hence do not have the funds to hire a full-time CUDA developer. Such companies tend to give out contracts to contractors or freelancers. Contractual work is almost similar to a full-time job, but it is only for a limited project. At the same time, freelancing is nothing like a full-time job. With freelancing, you do not need to always work in an office; you can work from the comfort of your home and at your desired time. Freelancers, unlike contractual workers, set their own rates. In the United Kingdom, a freelance CUDA developer charges, on average, US $39.07 (£ 28.21) per hour. Most freelancers work 4 to 8 hours a day, depending on the availability of projects.

CUDA Certification

To be a certified CUDA developer, you need to complete a CUDA certification course. Getting certified is vital in the new market. Companies prefer to hire certified developers for the roles. Getting a certification in CUDA is extremely easy. There are several courses available online which you can enroll in. By enrolling yourself in a CUDA certification course, you will learn step by step all you need to know about CUDA. The detailed video tutorials help you understand the concepts well. These certification courses help you to gain the practical skills needed to design solutions to real-world problems. A certified CUDA developer has much more market value and chances of getting hired.

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