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For simplicity, the number of float point operations is used to measure the computational complexity of the proposed algorithms.
More specifically, the PF algorithms have been implemented on GPU [14 16], and achieve significant speedup ratio over the implementations on the traditional CPU fashion but with no losing the performance for its float point computation ability.
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This chapter focuses on floating point approximations.
To solve the floating point data limitations.
To compute output Y, four floating point adders/subtractors and four floating point multipliers are required.
All of the floating point operations are single precision (32-bit) floating point operations.
It can support both floating point and fixed point operations.
A NIOS II soft core processor (Altera Corporation, San Jose, CA, USA) is instantiated and used in conjunction with dedicated single precision, 32-bit floating point custom instructions (floating point multiply, floating point subtract, and floating point addition).
The experiment is conducted with integer and floating point calculations.
back Thestep.
This work proposes designing of high speed floating point multipliers.
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