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在Freelancer上雇用a CUDA Developer
In simple terms “CUDA is an API Model and parallel computing platform which has been developed by NVIDIA”. CUDA enabled graphic processing unit which is used to carry out all-purpose function processing and is normally known as GPGPU.
Designing of CUDA is done to ensure its smooth compatibility and working with a number of programming languages including FORTRAN, C++, C and others. Direct 3D and OpenGL which were the formerly launched products of API solutions demanded highly developed and sophisticated set of skills in graphic programming. CUDA was released into market to provide an uncomplicated alternative for parallel programming experts to make the most of GPU resources. Programming frameworks like Open ACC and OpenCL are also supported by CUDA.
Windows XP, Windows Vista, Windows7, Linux and OS x are the supported operating systems with CUDA. Both 32-bit and 64-bit versions are well aided and facilitated by these operating systems. CUDA supports a range of applications like Badaboook (video calling), MotionDSP (vReal), Arcsoft (simHD), Cyberlink (PowerDirector &) and Pegasys (TMPGEnc 4.0 Xpress).
Benefits and Application of CUDA
Using graphic APIs CUDA is found to have numerous benefits over traditional purpose computation:
Amalgamated essential memory present in CUDA 4.0 version and succeeded versions.
Incorporated memory present in CUDA 6.0 version and latest versions
Pooled/ shared memory available to be mutually used amongst threads
Enabling quicker downloads and rapid checking of readbacks with GPU
It contains integer texture lookup offering complete help for bitwise and integers operations and working
Scattered reads enabling the code to be read from any arbitrary location in memory
CUDA has profound applications in countless fields including:
Finance and other calculation demanding fields
Due to an immensely rising need of CUDA experts 350 universities around the globe are offering relevant certifications. Hundreds and thousands of papers related to CUDA have been published and following programs are the latest upgrades to help improve individual skills and knowledge base.
CUDA Certification Program - the program aims at certifying specialists in massively parallel programming on GPUs. The certification is designed to meet up the rising demand of GPGPU engineers
CUDA Research Centres - this program acknowledges establishments that hold GPU Computing across multiple research fields
CUDA Teaching Centres - this officially imply institutions that have included GPU Computing techniques into their mainstream computer programming core curriculum
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