GPU Computing Seminar Report Covers:
- GPU Architecture
- GPU Computing
- Software environments
- Techniques and applications
Every CPU has its maximum clock limit. The Moore’s law says that more transistors can be set on the chips. Many of them have used more than one processor on the same chip,these more processors works on the basis ofparallelism. The processor that was used in the play station has attracted lots of people. GPU is designed for the computer that needs to do lots of work or require large processing. They are designed for the real time software that requires lots of calculation per second. It must support many operations that work in parallel.
They are developed with the user of graphics pipeline that will include the vertex operations, 3D based geometry. They will use techniques like rasterization, fragmentation operations. Newly developed GPU will have input assemblers that will be connected to the processor array that is connected to the raster operations or output mergers. Before that we need to setup the raster’s.
GUP Computing Architecture:
GPU uses multiple data programming on single programming. They can many programs in parallel. They can operate 32-bit integers. The main of the development of the GPU is the graphics. To deal with the graphics they have to use higher programming languages and shade’s They need to install DirectX 9 or higher version to run graphics successfully. They use lots of algorithms for the programming. You must have the knowledge of differential equation, linear algebra.
To run the GPU in your system you have at least Pentium 4 and NVIDIA GeForce 8800GTX. Another is Fast Fourier transformation. They are efficient algorithms and they deal with complex calculations. To run this you require Intel core 2 quad with the speed of 2.4GHz and NVIDIA GeForce 8800 GTX. They are the efficient application usually developed for the gaming.
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