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In computing, CUDA (Compute Unified Device Architecture) is a proprietary [2] parallel computing platform and application programming interface (API) that allows software to use certain types of graphics processing units (GPUs) for accelerated general-purpose processing, an approach called general-purpose computing on GPUs.
CuPy is an open source library for GPU-accelerated computing with Python programming language, providing support for multi-dimensional arrays, sparse matrices, and a variety of numerical algorithms implemented on top of them. [3]
AMD publicly discloses its set of 64-bit extensions to IA-32, called x86-64 (later branded AMD64). 2000 IBM ships its first 64-bit z/Architecture mainframe, the zSeries z900. z/Architecture is a 64-bit version of the 32-bit ESA/390 architecture, a descendant of the 32-bit System/360 architecture. 2001
In addition, four environments are provided containing native compilers, build tools and libraries that can be directly used to build native Windows 32-bit or 64-bit programs. The final programs built with the two native environments don't use any kind of emulation and can run or be distributed like native Windows programs.
OpenCL (Open Computing Language) is a framework for writing programs that execute across heterogeneous platforms consisting of central processing units (CPUs), graphics processing units (GPUs), digital signal processors (DSPs), field-programmable gate arrays (FPGAs) and other processors or hardware accelerators.
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A 32-bit register can store 2 32 different values. The range of integer values that can be stored in 32 bits depends on the integer representation used. With the two most common representations, the range is 0 through 4,294,967,295 (2 32 − 1) for representation as an binary number, and −2,147,483,648 (−2 31) through 2,147,483,647 (2 31 − 1) for representation as two's complement.
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