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Therefore, the process of increasing the number of cores significantly slowed down, and white university coats, for which two or four cores were clearly not enough, found a way to use other computing power for their scientific calculations, which was in abundance on the video card (as a result, even the BrookGPU tool appeared, emulating an additional processor using DirectX and OpenGL function calls). However, it turned out that making and designing multi-core processors is too difficult and expensive.Įach core had to house a full-fledged processor of a complex and confusing x86 architecture, with its own (rather large) cache, instruction pipeline, SSE blocks, many blocks performing optimizations, etc. This allowed the machines to perform several tasks at the same time, and the overall (theoretical) performance of the system increased exactly as many times as the number of cores was installed in the machine. Later, multi-core processors and multi-processor systems appeared, in which there were several such components.
#Movavi video converter 19 parallel gpu software#
Long time almost all mainstream PCs were equipped with a single processor that did every imaginable calculation, including the operating system code, all our software and viruses. We are all used to thinking that the only component of a computer capable of executing any code that is ordered to it is the central processor. And for Linux users, accustomed to "being in flight", and in general all this is seen as a dark forest. However, not everyone knows what these words mean and what the technologies behind them mean. Words like CUDA, Stream and OpenCL have become almost the most cited on the IT Internet in just two years.
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Today, news about the use of GPUs for general computing can be heard on every corner.