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Thursday, April 10, 2008

FPGA Vs DSP and FPGA applications

FPGA Vs DSP and FPGA applications
The DSP is a specialised microprocessor which is limited in performance by the clock rate, and the number of useful operations it can do per clock. In contrast, an FPGA is an uncommitted "sea of gates". The device is programmed by connecting the gates together to form multipliers, registers, adders and so forth. Using the Xilinx Core Generator this can be done at a block-diagram level. Many blocks can be very high level – ranging from a single gate to an FIR or FFT. Their performance is limited by the number of gates they have and the clock rate. Recent FPGAs have included Multipliers especially for performing DSP tasks more efficiently.
When sample rates grow above a few MHz, a DSP has to work very hard to transfer the data without any loss. This is because the processor must use shared resources like memory busses, or even the processor core which can be prevented from taking interrupts for some time. An FPGA on the other hand dedicates logic for receiving the data, so can maintain high rates of I/O.
The DSP can take a standard C program and run it. Most signal processing systems start life as a block diagram of some sort. Actually translating the block diagram to the FPGA may well be simpler than converting it to C code for the DSP.
Applications of FPGAs include digital signal processing, software-defined radio, aerospace and defense systems, ASIC prototyping, medical imaging, computer vision, speech recognition, cryptography, bioinformatics, computer hardware emulation and a growing range of other areas.
· FPGAs originally began as competitors to CPLDs and competed in a similar space, that of glue logic for PCBs. As their size, capabilities, and speed increased, they began to take over larger and larger functions to the state where some are now marketed as full systems on chips (SOC).
· FPGAs are increasingly used in conventional High Performance Computing applications where computational kernels such as FFT or Convolution are performed on the FPGA instead of a microprocessor. The use of FPGAs for computing tasks is known as reconfigurable computing.
· The current generation of FPGAs can implement around 100 single precision floating point units, all of which can compute a result every single clock cycle. The flexibility of the FPGA allows for even higher performance by trading off precision and range in the number format for an increased number of parallel arithmetic units. This has driven a new type of processing called reconfigurable computing.

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