S
sirisha
Guest
Arithmetic operations are among the most basic instructions in
microprocessors and many other ASICs. From SPECfp2000 benchmark, about
15% of the floating-point ALU operations are additions and about 10%
are subtractions. The most time consuming arithmetic operation is the
floating-point division, then comes to the multiplication and then the
addition/subtraction. The speed of those arithmetic operations
directly links to the overall performance of the ALU units and so the
computers. Since floating-point addition/subtraction units are built
on top of integer addition/subtraction units, performance of integer
addition/subtraction units have direct link to performance of
floating-point units.
In this class project, we design 2 32-bit addition/subtraction units,
one uses straight simple ripple-carry algorithm and the other uses
carry-looked-ahead algorithm. Our study will basically explore the
correlations between areas, speeds, algorithms and will at least cover
the information as listed below. All analyses will be performed based
on both theory and measurements and explanation will be provided for
discrepancies between the twos.
ƒ 1)Correlation of areas and speeds for both algorithms will be
determined
2)The two designs will be optimized for areas and analysis on speeds
will be performed
3)The two designs will be optimized for speeds and analysis on areas
will be performed
4)Costs and speeds of a 32-bit floating-point unit if the unit is
built based on one addition/subtraction algorithm versus the other
will be relatively evaluated
This project start with verilog code. I am unable to start the
code.I need help from group.
Thanks
sirisha.
microprocessors and many other ASICs. From SPECfp2000 benchmark, about
15% of the floating-point ALU operations are additions and about 10%
are subtractions. The most time consuming arithmetic operation is the
floating-point division, then comes to the multiplication and then the
addition/subtraction. The speed of those arithmetic operations
directly links to the overall performance of the ALU units and so the
computers. Since floating-point addition/subtraction units are built
on top of integer addition/subtraction units, performance of integer
addition/subtraction units have direct link to performance of
floating-point units.
In this class project, we design 2 32-bit addition/subtraction units,
one uses straight simple ripple-carry algorithm and the other uses
carry-looked-ahead algorithm. Our study will basically explore the
correlations between areas, speeds, algorithms and will at least cover
the information as listed below. All analyses will be performed based
on both theory and measurements and explanation will be provided for
discrepancies between the twos.
ƒ 1)Correlation of areas and speeds for both algorithms will be
determined
2)The two designs will be optimized for areas and analysis on speeds
will be performed
3)The two designs will be optimized for speeds and analysis on areas
will be performed
4)Costs and speeds of a 32-bit floating-point unit if the unit is
built based on one addition/subtraction algorithm versus the other
will be relatively evaluated
This project start with verilog code. I am unable to start the
code.I need help from group.
Thanks
sirisha.