Calculation of trigonometric functions in an integrated circuit device

Information

  • Patent Grant
  • 8589463
  • Patent Number
    8,589,463
  • Date Filed
    Friday, June 25, 2010
    14 years ago
  • Date Issued
    Tuesday, November 19, 2013
    11 years ago
Abstract
Circuitry for computing a trigonometric function of an input includes circuitry for relating the input to another value to generate an intermediate value, circuitry for selecting one of the input and the intermediate value as a trigonometric input value, circuitry for determining respective initial values of a plurality of trigonometric functions for the trigonometric input value, and circuitry for deriving, based at least in part on a trigonometric identity, a final value of the first trigonometric function from the respective initial values of the plurality of trigonometric functions. The trigonometric function may be any of sine, cosine and tangent and their inverse functions. The trigonometric identities used allow a computation of a trigonometric function to be broken into pieces that either are easier to perform or can be performed more accurately.
Description
BACKGROUND OF THE INVENTION

This invention relates to calculating trigonometric functions in integrated circuit devices, and particularly in programmable integrated circuit devices such as programmable logic devices (PLDs).


Trigonometric functions are generally defined for the relatively small angular range of 0-360°, or 0-2π radians. For angular values above 2π, the values of the trigonometric functions repeat. Indeed, one could restrict the range to 0-π/2, because various trigonometric identities can be used to derive values for trigonometric functions of any angle between π/2 and 2π from trigonometric functions of angles between 0 and π/2.


One method that may be used in integrated circuit devices for calculating trigonometric functions is the CORDIC algorithm, which uses the following three recurrence equations:

xn+1=xn−dnyn2−n
yn+1=yn+dnxn2−n
zn+1=zn−dn tan−1(2−n)

For example, to calculate a sine or cosine of an input, the x value is initialized to “1”, the y value is initialized to “0”, and the Z value is initialized to the angle required. Z is then rotated towards zero, which determines the sign of dn, which is ±1—if zn is positive, then so is dn, as the goal is to bring z closer to 0; if zn is negative, then so is dn, for the same reason. x and y represent the x and y components of a unit vector; as z rotates, so does that vector, and when z has reached its final rotation to 0, the values of x and y will have converged to the cosine and sine, respectively, of the input angle.


To account for stretching of the unit vector during rotation, a scaling factor is applied to the initial value of x. The scaling factor is:










n
=
0






1
+

2


-
2


n





=

1.64676025812106564












The initial x is therefore be set to 1/1.64677 . . . =0.607252935 . . . .


However, CORDIC may become inaccurate as the inputs become small. For example, the actual value of sin(θ) approaches θ as θ approaches 0 (and therefore sin(θ) approaches 0), and the actual value of cos(θ) approaches 1 as θ approaches 0. However, the magnitude of the error between the calculated and actual values increases as θ decreases.


Moreover, while CORDIC on initial consideration appears to be easily implemented in integrated circuit devices such as FPGAs, closer analysis shows inefficiencies, at least in part because of multiple, deep arithmetic structures, with each level containing a wide adder. Common FPGA architectures may have 4-6 input functions, followed by a dedicated ripple carry adder, followed by a register. When used for calculating floating point functions, such as the case of single precision sine or cosine functions, the number of hardware resources required to generate an accurate result for smaller input values can become large.


SUMMARY OF THE INVENTION

According to embodiments of the present invention, different trigonometric functions may be computed using various modified implementations that are based on different trigonometric identities that can be applied.


For sine and cosine functions, a modified CORDIC implementation changes small input angles to larger angles for which the CORDIC results are more accurate. This may be done by using π/2−θ instead of θ for small θ (e.g., for θ<π/4). As discussed above, CORDIC accuracy suffers for smaller angles, but a standard CORDIC implementation may be used for larger angles. A multiplexer can select between the input value θ and the output of a subtractor whose subtrahend and minuend inputs are, respectively, π/2 and the input value θ. A comparison of the input θ to a threshold can be used to control the multiplexer to make the selection. Both sine and cosine are computed by the x and y datapaths of the CORDIC implementation and the desired output path can be selected using another multiplexer, which may be controlled by the same comparison output as the input multiplexer. When π/2−θ has been used as the input, the identities cos(θ)=sin(π/2−θ) and sin(θ)=cos(π/2−θ) can be used to derive the desired result.


For the tangent function, the input angle can be broken up into the sum of different ranges of bits of the input angle, using trigonometric identities for the tangent of a sum of angles. Because some of the component ranges will be small, the identities will be simplified relative to those component ranges. The identities can be implemented in appropriate circuitry.


For the inverse tangent (i.e., arc tan or tan−1) function, the problem is that the potential input range is between negative infinity and positive infinity (unlike, e.g., inverse sine or inverse cosine, where the potential input range is between −1 and +1). In accordance with the invention, trigonometric identities involving the inverse tangent function can be used to break up the input into different ranges, with the most complicated portion of the identity having a contribution below the least significant bit of the result, so that it can be ignored. The identities can be implemented in appropriate circuitry.


For inverse cosine (i.e., arc cos or cos−1), the following identity may be used:







arccos
=

2


arctan
(



1
-

x
2




1
+
x


)



,





which may be reduced to:







arccos
=

2


arctan
(


1
-
x



1
-

x
2




)



,





The inverse tangent portion may be calculated as discussed above, simplified because the input range for inverse cosine is limited to between 0 and 1. Known techniques may be used to calculate the inverse square root. For inverse sine (i.e., arcsin or sin−1), which also has an input range limited to between 0 and 1, the inverse cosine can be calculated and then subtracted from π/2, based on the identity arc sin(x)=π/2−arc cos(x).


Therefore, in accordance with the present invention there is provided circuitry for computing a trigonometric function of an input. The circuitry includes circuitry for relating the input to another value to generate an intermediate value, circuitry for selecting one of the input and the intermediate value as a trigonometric input value, circuitry for determining respective initial values of a plurality of trigonometric functions for the trigonometric input value, and circuitry for deriving, based at least in part on a trigonometric identity, a final value of the first trigonometric function from the respective initial values of the plurality of trigonometric functions.


A corresponding method for configuring an integrated circuit device as such circuitry is also provided. Further, a machine-readable data storage medium encoded with instructions for performing the method of configuring an integrated circuit device is provided.





BRIEF DESCRIPTION OF THE DRAWINGS

Further features of the invention, its nature and various advantages will be apparent upon consideration of the following detailed description, taken in conjunction with the accompanying drawings, in which like reference characters refer to like parts throughout, and in which:



FIG. 1 shows a first embodiment of a CORDIC implementation for calculating sine and/or cosine in accordance with the present invention;



FIG. 2 shows a second embodiment of a CORDIC implementation for calculating sine and/or cosine in accordance with the present invention;



FIG. 3 shows a third embodiment of a CORDIC implementation for calculating sine and/or cosine in accordance with the present invention;



FIG. 4 shows a fourth embodiment of a CORDIC implementation for calculating sine and/or cosine in accordance with the present invention;



FIG. 5 shows an embodiment of an implementation for calculating tangent in accordance with the present invention;



FIG. 6 shows a first range of the inverse tangent function;



FIG. 7 shows a second range of the inverse tangent function;



FIG. 8 shows a third range of the inverse tangent function;



FIG. 9 shows an embodiment of an implementation for calculating inverse tangent in accordance with the present invention;



FIG. 10 shows a first portion of an embodiment of an implementation for calculating inverse cosine and/or inverse sine in accordance with the present invention;



FIG. 11 shows a second portion of an embodiment of an implementation for calculating inverse cosine and/or inverse sine in accordance with the present invention;



FIG. 12 is a cross-sectional view of a magnetic data storage medium encoded with a set of machine-executable instructions for performing the method according to the present invention;



FIG. 13 is a cross-sectional view of an optically readable data storage medium encoded with a set of machine executable instructions for performing the method according to the present invention; and



FIG. 14 is a simplified block diagram of an illustrative system employing a programmable logic device incorporating the present invention.





DETAILED DESCRIPTION OF THE INVENTION

As discussed above, in a standard CORDIC implementation:

xn+1=xn−dnyn2−n
yn+1=yn+dnxn2−n
zn+1=zn−dn tan−1(2−n)

As can be seen from these equations, at the first level (for n=0):

x1=x0−y0
y1=y0+x0
z1=z0−tan−1(1)

Similarly, at the second level (for n=1):

x2=x1−d1(y1/2)
y2=y1+d1(x1/2)
z2=z1−d1 tan−1(0.5)

It will be understood that this continues for additional n until zn converges to 0, or as close to 0 as required by a particular implementation. However, as discussed above, the accuracy of a CORDIC implementation decreases as the input angle becomes small.


A logical structure 100 of a first embodiment according to the present invention for implementing CORDIC for sine or cosine is shown in FIG. 1. Structure 100 may be implemented as circuitry. Structure 100 is built around a CORDIC engine 101 which may be any suitable CORDIC engine, including that described in copending, commonly-assigned U.S. patent application Ser. No. 12/722,683, filed Mar. 12, 2010, which is hereby incorporated by reference herein in its entirety. CORDIC engine 101 provides an x output 111 which generally represents the cosine of the input, as well as a y output 112 which generally represents the sine of the input.


Input multiplexer 102 selects either the input variable 103, or difference 104 between π/2 and input variable 103. The control signal 105 for input multiplexer 102 result from a comparison 106 that which indicate(s) whether input variable 103 (θ) is greater than π/4 or less than π/4 (or whatever other threshold may be selected). Because input variable 103 preferably is expressed a fraction (impliedly multiplied by π/2), the comparison may be performed simply by examining one or more of the most significant bits of input variable 103. Alternatively, a more complex comparison may be made.


In any event, the value passed to CORDIC engine is either θ or π/2−θ, depending on whether θ is greater than (or equal to) or less than π/4.


The same control signal 105 that determines the input to CORDIC engine 101 helps to determine which output 111, 121 is selected by output multiplexer 107. Specifically, cos(θ)=sin(π/2−θ) and sin(θ)=cos(π/2−θ). Additional input 115 may be provided that represents whether the desired output is sine or cosine, and that input is combined at 125 with input 105, to provide a control signal 135, so that if input variable 103 (θ) was used as the CORDIC input directly, then output 111 is selected if the desired function is cosine and output 112 is selected if the desired function is sine. But if difference 104 (π/2−θ) was used as the CORDIC input, then output 112 is selected if the desired function is cosine and output 111 is selected if the desired function is sine.


Known techniques for speeding up CORDIC calculations can be used. For example, once about halfway through the CORDIC calculation of a sine value, the final value of y can be approximated by multiplying the then-current value of x by the then-current value of z, and then subtracting that product from the then-current value of y. Similarly, for cosine, the final value of x can be approximated by multiplying the then-current value of y by the then-current value of z and adding that product to the then-current value of x. This may be referred to as “terminated CORDIC.” FIG. 2 shows a modified CORDIC structure 200 that implements terminated CORDIC in accordance with an embodiment of the invention. Structure 200 may be implemented as circuitry.


The input stage of structure 200 is identical to that of structure 100, including input multiplexer 102, input variable 103, difference 104, comparison circuit 106 and control signal 105. CORDIC engine 201 may be the same as CORDIC engine 101, except that the z datapath is used as an output 211, in addition to outputs 111, 121.


However, the output stage of structure 200 differs from the output stage of structure 100. Instead of one output multiplexer 106, there is a first output multiplexer 206 controlled by signal 135 and a second output multiplexer 216 controlled by the inverse of signal 135. For cosine, this arrangement provides x directly to adder/subtractor 208, and provides y and z to multiplier 207, which provides its output to adder/subtractor 208. For sine, this arrangement provides y directly to adder/subtractor 208, and provides x and z to multiplier 207, which provides its output to adder/subtractor 208.


In some embodiments, structure 100 or 200 may be implemented in a programmable device, such as an FPGA, either in programmable logic, or in a combination of programmable logic and fixed logic (e.g., adders and/or multipliers) if provided. For example, FPGAs in the STRATIX® family of FPGAs available from Altera Corporation, of San Jose, Calif., include digital signal processing blocks having multipliers and adders and programmable interconnect for connecting the multipliers and adders. Such an FPGA may be configured to use the adders and/or multipliers, as well as any programmable logic that may be needed, to implement structure 100 or 200.


The input range can be further limited to a smaller range between π/8 and π/4, which may provide a more accurate CORDIC result than a range between π/4 and π/2. According to such an implementation, which may be carried out using a structure 300 as shown in FIG. 3, which may be implemented as circuitry, when the input is between 0 and π/8, the input is subtracted from π/4, creating a new value between π/8 and π/4. When the input is between 3π/8 and π/2, π/4 is subtracted from the input, also creating a new value between π/8 and π/4. If the input is between π/8 and 3π/8, the input may be passed through unchanged.


As seen in FIG. 3, input multiplexer 302 selects either input 303, or the difference 304 between π/4 and input 303, or the difference 314 between input 303 and π/4. The selected input is used in CORDIC engine 301 which may be substantially identical to CORDIC engine 101.


For the case where difference 304 is used, the outputs of CORDIC engine 301 are processed by output stage 320 in accordance with the following identities:

sin(A−B)=sin(A)cos(B)−sin(B)COS(A)
cos(A−B)=cos(A)cos(B)+sin(A)sin(B)

If A=π/4, and B=π/4−θ, then A−B=π/4−(π/4−θ)=θ. Also, SIN(π/4)=COS (π/4)=2−0.5.


It follows, then, that:










SIN


(
θ
)


=



SIN


(

A
-
B

)








=





SIN


(

π
/
4

)




COS


(


π
/
4

-
θ

)



-


SIN


(


π
/
4

-
θ

)




COS


(

π
/
4

)










=




2

-
0.5





(


COS


(


π
/
4

-
θ

)


-

SIN


(


π
/
4

-
θ

)



)

.










Similarly:










COS


(
θ
)


=



COS


(

A
+
B

)








=





COS


(

π
/
4

)




COS


(


4
/
θ

-
π

)



+


SIN


(


π
/
4

-
θ

)




SIN


(

π
/
4

)










=




2

-
0.5





(


COS


(


π
/
4

-
θ

)


+

SIN


(


π
/
4

-
θ

)



)

.









For the case where difference 314 is used, the outputs of CORDIC engine 301 are processed by output stage 320 in accordance with the following identities:

sin(A+B)=sin(A)cos(B)+sin(B)COS(A)
cos(A+B)=cos(A)cos(B)−sin(A)sin(B)

If A=π/4, and B=θ−π/4, then A+B=π/4+(θ−π/4)=θ. Again, SIN(π/4)=COS (π/4)=2−0.5.


It follows, then, that:










SIN


(
θ
)


=



SIN


(

A
+
B

)








=





SIN


(

π
/
4

)




COS


(

θ
-

π
/
4


)



+


SIN


(

θ
-

π
/
4


)




COS


(

π
/
4

)










=




2

-
0.5





(


COS


(

θ
-

π
/
4


)


+

SIN


(

θ
-

π
/
4


)



)

.










Similarly:










COS


(
θ
)


=



COS


(

A
+
B

)








=





COS


(

π
/
4

)




COS


(

θ
-

π
/
4


)



-


SIN


(

θ
-

π
/
4


)




SIN


(

π
/
4

)










=




2

-
0.5





(


COS


(

θ
-

π
/
4


)


-

SIN


(

θ
-

π
/
4


)



)

.









This is implemented in output stage 320 by adder/subtractor 321 which adds the y (SIN) datapath to, or subtracts it from, the x (COS) datapath, and by multiplier 322 which multiplies that difference by 2−0.5 (indicated in FIG. 3 as SIN(π/4)). Output stage 320 also may include a multiplexing circuit 323 (similar to the combination of multiplexers 206, 216 in FIG. 2) for implementing the pass-through of the correct datapath (SIN or COS, depending on the desired function) for a case where the input 303 is between π/8 and 3π/8 and was passed through input multiplexer 302 unchanged.


Thus, as compared to embodiment 100 of FIG. 1, only one additional subtractor and one additional constant multiplication are needed for increased accuracy.


Alternatively, if the input is between π/4 and 3π/8, it also falls under embodiment 100 of FIG. 1, and it can be reflected around π/4 by subtracting the input from π/2, switching SIN and COS results to get the desired output. This also may be useful for implementing other types of algorithms to calculate SIN and COS values where a small input range can be used to improve the convergence rate.


A “terminated CORDIC” implementation similar to embodiment 200 of FIG. 2 can be used with embodiment 300 of FIG. 3. Such an implementation 400 is shown in FIG. 4.


In a case where signal 105 selects the direct input 408, then, as in embodiment 200, only one of the SIN/COS datapaths 401, 402 is multiplied at 411, 412 by the z datapath 403 and then, at 421, is added to or subtracted from the other of the SIN/COS datapaths 401, 402, and that result is multiplied at 422 by 2−0.5. Whether datapath 401 or 402 is multiplied by datapath 403 is determined by signal(s) 435, output by logic 425 which, based on comparison signal 105 and signal 115 which indicates whether sine or cosine is desired, causes one of multiplexers 413, 423 to select datapath 403 for input to a respective one of multipliers 411, 412, and other of multiplexers 413, 423 to select the value ‘1’ for input to the other respective one of multipliers 411, 412. In this case, signal(s) 435 also determines whether adder/subtractor 421 adds or subtracts, and causes multiplexer 443 to select the value ‘0’ for addition at 453 to sum/difference 421. Sum 453 is then multiplied by sin(π/4) (i.e., 2−0.5) at 422.


In a case where signal 105 selects difference input 404 (π/4−θ), because input 408 is less than π/8, then, depending on whether sine or cosine is desired, the following relationships, as discussed above, will apply:

SIN(θ)=2−0.5(COS(π/4−θ)−SIN(π/4−θ))
COS(θ)=2−0.5(COS(π/4−θ)+SIN(π/4−θ))

Similarly, in a case where signal 105 selects difference input 444 (θ−π/4), because input 408 is greater than 3π/8, then, depending on whether sine or cosine is desired, the following relationships, as discussed above, will apply:

SIN(θ)=2−0.5(COS(θ−π/4)+SIN(θ−π/4))
COS(θ)=2−0.5(COS(θ−π/4)−SIN(θ−π/4))


In a terminated CORDIC implementation,

COS(•)=x+yz
SIN(•)=y−xz

Therefore, in a terminated CORDIC case where signal 105 selects difference input 404 (π/4−θ),













SIN


(
θ
)


=




2

-
0.5




(

x
+
yz
-

(

y
-
xz

)


)








=




2

-
0.5




(

x
-
y
+

(

yz
+
xz

)


)




















COS


(
θ
)


=




2

-
0.5




(

x
+
yz
+

(

y
-
xz

)


)








=




2

-
0.5




(

x
+
y
+

(

yz
-
xz

)


)


















Similarly, in a terminated CORDIC case where signal 105 selects difference input 444 (θ−π/4),










SIN


(
θ
)


=




2

-
0.5




(

x
+
yz
+

(

y
-
xz

)


)








=




2

-
0.5




(

x
+
y
+

(

yz
-
xz

)


)















COS


(
θ
)


=




2

-
0.5




(

x
+
yz
-

(

y
-
xz

)


)








=




2

-
0.5




(

x
-
yz
+

(

y
+
xz

)


)









For these implementations, signal(s) 435 would cause both of multiplexers 413, 423 to select datapath 403 for input to multipliers 411, 412. Signal(s) 435 also would determine whether adders/subtractors 421 and 431 add or subtract, respectively, and would causes multiplexer 443 to select the sum/difference 431 for addition at 453 to sum/difference 421. Sum 453 is then multiplied by sin(π/4) (i.e., 2−0.5) at 422.


When implementing embodiment 400 in one of the aforementioned STRATIX® FPGAs, one of the aforementioned digital signal processing blocks, having multipliers and adders, can be used at 410 to provide multipliers 404, 405 and adder/subtractor 406. The digital signal processing blocks of such FPGAs, for example, are well-suited for performing two 36-bit-by-18-bit multiplications which may be used for this purpose. One such implementation is described at page 5-21 of the Stratix III Device Handbook, Volume 1 (ver. 2, March 2010), published by Altera Corporation, which is hereby incorporated by reference herein.


Other identity-based approaches can be used to simplify the calculations of other trigonometric functions.


For example, for tan(θ), the normalized or range-reduced input is −π/2≦θ≦π/2, while the output is between negative infinity and positive infinity. The following identity holds true for the tangent function:







tan


(

a
+
b

)


=



tan


(
a
)


+

tan


(
b
)




1
-


tan


(
a
)


×

tan


(
b
)










By judiciously breaking up θ, one can break up the problem of calculating tan(θ) into easily calculable pieces. In this case, it may be advantageous to break up tan(θ) into three pieces. This case be done by substituting c for b, and a+b for a, above. Thus:







tan


(

a
+
b
+
c

)


=



tan


(

a
+
b

)


+

tan


(
c
)




1
-


tan


(

a
+
b

)


×

tan


(
c
)










Expanding further:







tan


(

a
+
b
+
c

)


=





tan


(
a
)


+

tan


(
b
)




1
-


tan


(
a
)


×

tan


(
b
)





+

tan


(
c
)




1
-


(



tan


(
a
)


×

tan


(
b
)




1
-


tan


(
a
)


×

tan


(
b
)





)

×

tan


(
c
)









Although this looks much more complex than the original identity, the properties of the tangent function, and the precision of single precision arithmetic, can be used to greatly simplify the calculation.


As with many trigonometric functions, tan(θ)≈θ for small θ. The input range for the tangent function is defined as −π/2≦θ≦π/2. In single precision floating point arithmetic—e.g., under the IEEE754-1985 standard—the exponent is offset by 127 (i.e., 20 becomes 2127). If the input exponent is 115 or less (i.e., a true exponent of −12 or less), the error between tan(x) and x is below the precision of the number format, therefore below that value, tan(θ) can be considered equal to θ.


The tangent function is therefore defined for a relatively narrow exponent range, between 115 and 127, or 12 bits of dynamic range. For IEEE754-1985 arithmetic, the precision is 24 bits. The input number can therefore be represented accurately as a 36-bit fixed point number (24 bits precision+12 bits range).


Such a 36-bit fixed point number can then be split into three components. If θ=a+b+c as indicated above, the upper 9 bits can be designated the c component, the next 8 bits can be designated the a component, and 19 least significant bits may be designated the b component.


As discussed above, tan(θ)=θ for any value of θ that is smaller than 2−12. As the 19 least significant bits of a 36-bit number, b is smaller than 2−17. Therefore, tan(b)=b and we can write:







tan


(

a
+
b
+
c

)


=





tan


(
a
)


+
b


1
-


tan


(
a
)


×
b



+

tan


(
c
)




1
-


(



tan


(
a
)


+
b


1
-


tan


(
a
)


×
b



)

×

tan


(
c
)









The tangent of a is relatively small. The maximum value of a is slightly less than 0.0039062510 (tan(a)=0.0039062710) and the maximum value of b is 0.0000152610, which is also its tangent. Therefore, the maximum value of tan(a)×b is 5.96×10−8, therefore the minimum value 1−tan(a)×b=0.9999999410. The maximum value of tan(a)+b is 0.0039215286610. The difference between that value, and that value divided by the minimum value of 1−tan(a)×b is 2.35×10−10, or about 32 bits, which is nearly the entire width of a, b and c combined. In the worst case, where c is zero, this error would not be in the precision of the result either, which is only 24 bits.


The foregoing equation therefore can be further simplified to:







tan


(

a
+
b
+
c

)


=



tan


(
a
)


+
b
+

tan


(
c
)




1
-


(


tan


(
a
)


+
b

)

×

tan


(
c
)










Insofar as a and c are 8 and 9 bits respectively, the tangents for all possible bit combinations can be stored in a table with 36-bit data. Therefore the problem is reduced to a 36-bit fixed point multiplication, a 36-bit fixed point division, and a fixed point subtraction, although the additions are floating point additions as described below.


An embodiment 500 of this tangent calculation is shown in FIG. 5 and may be implemented in circuitry.


The input value 501 (θ) is first converted to a 36-bit fixed-point number by shifting at 502 by the difference 503 between its exponent and 127 (the IEEE754-1985 exponent offset value). The converted fixed-point input 504 is then split into three numbers: c—bits [36:28], a—bits [27:20], and b—bits [19:1]. Tan(c) is determined in lookup table 505 and tan(a) is determined in lookup table 506. Tan(a) and b, which are both in fixed-point format, are added at 507. That sum must then be normalized to the exponent of c, which can range from 0 to 19 (127 to 146 in single precision offset equivalent). The ‘tan(a)+b’ sum has a maximum exponent of −8 (119 in single precision offset equivalent), and is normalized at 508 for multiplying by tan(c) at 509 (for the denominator) and adding to tan(c) at 510 (for the numerator).


The numerator is normalized at 511 and now exists as a floating-point number. The local exponent (‘15’−‘c exponent’+‘a+b exponent’) is a number that is relative to ‘1.0’, and is used to denormalize the product to a fixed point number again at 512.


The denominator product is subtracted from ‘1’ at 513. The difference is normalized at 514. The difference is then inverted at 515 to form the denominator.


The denominator is multiplied by the numerator at 516. Before that multiplication, the numerator exponent is normalized at 517. The exponent is ‘119’ (which is the minimum value of c, or the maximum value of b—the reference point to which the internal exponents are normalized) plus the numerator exponent plus the denominator exponent. The denominator exponent is the shift value from the final denominator normalization 514—normally this would be considered a negative relative exponent, and subtracted from any final exponent. However, because the denominator is arithmetically inverted immediately following the normalization, the exponent is converted from negative to positive, and can therefore be added at this stage.


The result is rounded at 518 and is ready for use. However, if the exponent of the original input value 501 is less than 115, the output and the input are considered the same—i.e., tan(θ)=θ. This is implemented with the multiplexer 519, which selects as the final output either the rounded calculation result 520, or input 501, based on control signal 521 which is determined (not shown) by the size of the exponent of input 501.


For inverse tangent (i.e., arc tan(x) or tan−1(x), the situation is reversed in that the input is between negative infinity and positive infinity, while the normalized or range-reduced output is −π/2≦θ≦π/2. Once again, the problem can be broken down into input ranges. Thus, as shown in FIG. 6, for −1≦x≦+1, arc tan(x) is relatively linear, and has an output in the range −π/4≦θ≦+π/4. Viewed on an intermediate scale in FIG. 7, for −1010≦x≦+1010, arc tan(x) shows inflection points past ±1, flattening out to an output in the range −π/2≦θ≦+π/2. Viewed on a larger scale in FIG. 8, for −10010≦x≦+10010, arctan(x) remains in an output range of −π/2≦θ≦+π/2. In IEEE754-1985 single-precision arithmetic, with 24 bits of precision and an exponent up to 127, the output must be exact for a set of 833860810 (223) points in 127 segments along the input curve.


The calculation can be simplified by separately handling inputs of magnitude less than 1 and inputs of magnitude greater than 1.


Considering first inputs of magnitude less than 1, the following identity may be applied:







arctan


(
a
)


=


arctan


(
b
)


+

arctan


(


a
-
b


1
+
ab


)








If b is close enough to a, then c=(a−b)/(1+ab) is very small and arc tan(c)≈c. If a has a maximum value of 1, and b is made equal to the 8 or 10 most significant bits of a, then c will have a maximum value of 1/256 for 8 bits, or 1/1024 for 10 bits. The inverse tangent 1/256 (0.0039062510) is 0.0039062310. The error is almost at the floor of the precision of the input (23 bits). The inverse tangent of 1/1024 (0.000976562510) is 0.00097652210, which has an error below the least significant bit of the input range.


The subrange b can easily be separated from a by truncation. The (a−b) term is made up of the truncated bits. ab will always be less than 1, so the term 1+ab can be calculated without an adder, by directly concatenating a ‘1’ to the ab term. c can therefore be calculated easily. Values for arc tan(b) where b<1 can be stored in a lookup table. Therefore, arc tan(a) can be determined by looking up arc tan(b) in the table and adding c to the lookup result.


If a is greater than (or equal to) 1, then the following identity can be used:







arctan


(
a
)


=


π

2






-

arctan


(

1
a

)








The inverse tangent of the inverse of the input may be determined as described above for inputs less than 1 and then the desired result is obtained by subtracting from π/2.


The input mantissa is converted to a 36-bit number, by appending a ‘1’ to the left of the most significant bit, and appending a number of ‘0’ bits to the right of the least significant bit. The exponent of this number is 127−(input_exponent −127)−1=253−input_exponent. Once the correct floating point input has been selected, the number is converted to a fixed point equivalent by right shifting it from the reference point of 1. This should not reduce accuracy of the result given that 36-bit numbers are used. If the number has an exponent of 117 (for a right shift of 10 bits), there will still be 26 valid bits in the 36-bit magnitude, and only 24 bits are needed for single-precision floating point representation.


An embodiment 900 of this inverse tangent calculation is shown in FIG. 9 and may be implemented in circuitry.


The mantissa of the input number (with leading ‘1’ and trailing zero(es) appended as discussed above is input at 901, while the exponent of the input number is input at 902. Multiplexers 903, 904 select the unaltered input mantissa and exponent if the input value is less than 1.0 as determined at 905. Otherwise, multiplexers 903, 904 select inverse 906 and the new exponent (original exponent subtracted from ‘253’). Inverse 906 can be computed using any suitable inverse calculation module 907. The input is then normalized at 908 to a fixed-point representation 909.


The uppermost bits 910 are input to lookup table 911 and are also input to multiplier 912 along with all bits 913—this is the ab calculation discussed above. a−b is the remaining bits 914.


The ab product 915 is added to ‘1’ at 916 to form the 1+ab sum 917 which is inverted, again using any suitable inversion module 918 to form 1/(1+ab) quotient 919, which is multiplied at 920 by a−b term 914, forming the c term (a−b)/(1+ab). c term 921 is added at 922 to arc tan(b) as determined in lookup table 911.


If the original input was less than ‘1’, then sum 922 is the result, which is selected by control signal 905 at multiplexer 923 following normalization at 924. Sum 922 is also subtracted from π/2 at 925 and normalized at 926, and if the original input was greater than (or equal to) ‘1’, then difference 925, as normalized at 926, is the result, which is selected by control signal 905 at multiplexer 923. Any necessary rounding, exception handling, etc., is performed at 927 to provide result 928.


In the input range of exponents 115-120 (as an example), some inaccuracies in the output (still limited to a small number of least significant bits) may occur. One way to solve this is to use a second, smaller lookup table (not shown) for a limited subset of most significant valid bits—e.g., 6 bits. The b value would be the upper 6 bits of the subrange, and the a−b value would be the lower 20 bits. To maintain the maximum amount of precision, the table could contain results that are normalized to the subrange—for example if the largest exponent in the subrange were 120, then 1.999910×2120 would be a fully normalized number, with all other table entries relative to that one. The c value would have to be left-shifted so that it would have the correct magnitude in relation to the b table output. One way (and possibly the most accurate way) to implement this would be to take the a−b value from before the fixed point shifter. That is, instead of fixed-point representation 909, the output of multiplexer 903 could be used directly. An additional multiplexer (not shown) could be provided to select between the output of multiplexer 903 for smaller exponents and the output of normalizer 908 for larger exponents.


Once inverse tangent can be calculated, inverse cosine and inverse sine can easily be calculated based on:







arccos


(
x
)


=

2


arctan


(


1
-
x



1
-

x
2




)








and

arc sin(x)=π/2−arc cos(x).


An embodiment 1000 of the inverse cosine calculation is shown in FIG. 10 and may be implemented in circuitry.


The input argument x is input as sign 1001, mantissa 1002 and exponent 1003 to preprocessing module 1100, shown in more detail in FIG. 11. Preprocessing module 1100 prepares the 1−x numerator term 1004 and the 1−x2 denominator term 1005 from x. The inverse square root of denominator term 1005 is taken at inverse square root module 1006, which be any suitable inverse square root module.


The mantissa 1007 of the inverse square root is multiplied at 1008 by the mantissa 1009 of the numerator term, while the exponent 1010 of the inverse square root is added at 1011 to the exponent 1012 of the numerator term, and ‘127’ is subtracted from the exponent at 1013. The result is input to an inverse tangent module 1014 which may be inverse tangent module 900, above.


The inverse tangent module 1014 outputs a 36-bit fixed point value between 0 and π/2. If the input number is positive, the inverse cosine of that input must lie in the first (or fourth) quadrant, and the output of inverse tangent module 1014 is used directly. This is implemented by exclusive-OR gate 1024 and AND-gate 1034. Sign bit 1001 will be a ‘0’, meaning that XOR gate 1024 will pass the output of inverse tangent module 1014 without change, and there will be no contribution at adder 1044 from AND-gate 1034. If the input number is negative, the inverse cosine of that input must lie in the second (or third) quadrant. In that case, the inverse cosine value can be calculated by subtracting the output of inverse tangent module 1014 from π. Sign bit 1001 will be a ‘1’, meaning that XOR gate 1024 will pass the 1's-complement negative of the output of inverse tangent module 1014, while AND-gate 1034 will pass the value π. The sign bit is also used as a carry input (not shown) to adder 1044, converting the 1's-complement number to 2's-complement format, and adder 1044 outputs the difference between π and the output of inverse tangent module 1014.


Output 1015 is the inverse cosine. By subtracting inverse cosine output 1015 from π/2 at 1016, inverse sine 1017 can be determined. However, for inputs having real exponents less than −12 (IEEE754-1985 exponents less than 115), it would be more accurate to rely on arc sin(x)≈x than to rely on the calculated value.



FIG. 11 shows preprocessing module 1100, including numerator portion 1101 and denominator portion 1102. The input mantissa (with leading ‘1’ and trailing zero(es)) is input to numerator portion 1101 at 1103 and to denominator portion 1102 at 1104, while the input exponent is input to numerator portion 1101 at 1105 and to denominator portion 1102 at 1106.


On the numerator side, ‘127’ is subtracted from the exponent at 1107 to determine the “real” exponent, which is then used in shifter 1108 to turn the input mantissa into a fixed-point number 1109, which is subtracted at 1110 from ‘1’ to yield the numerator 1−x. The number of leading zeroes in the result are counted at count-leading-zeroes module 1111 and used at shifter 1112 to normalize the numerator mantissa and at subtractor 1113 to determine the IEEE754-1985 exponent by subtracting from ‘127’.


On the denominator side, the input mantissa is multiplied by itself at multiplier 1114 to determine x2 value 1115. The input exponent is left-shifted by one place at 1116 and subtracted from ‘253’ at 1117 to determine how far to right-shift value 1115 at 1118 to yield a fixed-point representation of x2. The fixed-point representation of x2 is subtracted from ‘1’ at 1119 to yield denominator 1−x2 at 1120. The number of leading zeroes in value 1120 are counted at count-leading-zeroes module 1121 and used at shifter 1122 to normalize the denominator mantissa and at subtractor 1123 to determine the IEEE754-1985 exponent by subtracting from ‘127’.


The trigonometric function calculating structures described above can be implemented as dedicated circuitry or can be programmed into programmable integrated circuit devices such as FPGAs. As discussed, in FPGA implementations, certain portions of the circuitry, particularly involving multiplications and combinations of multiplications as indicated, can be carried out in specialized processing blocks of the FPGA, such as a DSP block, if provided in the FPGA.


Instructions for carrying out a method according to this invention for programming a programmable device to implement the trigonometric function calculating structures described above may be encoded on a machine-readable medium, to be executed by a suitable computer or similar device to implement the method of the invention for programming or configuring PLDs or other programmable devices to perform addition and subtraction operations as described above. For example, a personal computer may be equipped with an interface to which a PLD can be connected, and the personal computer can be used by a user to program the PLD using a suitable software tool, such as the QUARTUS® II software available from Altera Corporation, of San Jose, Calif.



FIG. 12 presents a cross section of a magnetic data storage medium 1200 which can be encoded with a machine executable program that can be carried out by systems such as the aforementioned personal computer, or other computer or similar device. Medium 1200 can be a floppy diskette or hard disk, or magnetic tape, having a suitable substrate 1201, which may be conventional, and a suitable coating 1202, which may be conventional, on one or both sides, containing magnetic domains (not visible) whose polarity or orientation can be altered magnetically. Except in the case where it is magnetic tape, medium 1200 may also have an opening (not shown) for receiving the spindle of a disk drive or other data storage device.


The magnetic domains of coating 1202 of medium 1200 are polarized or oriented so as to encode, in manner which may be conventional, a machine-executable program, for execution by a programming system such as a personal computer or other computer or similar system, having a socket or peripheral attachment into which the PLD to be programmed may be inserted, to configure appropriate portions of the PLD, including its specialized processing blocks, if any, in accordance with the invention.



FIG. 13 shows a cross section of an optically-readable data storage medium 1210 which also can be encoded with such a machine-executable program, which can be carried out by systems such as the aforementioned personal computer, or other computer or similar device. Medium 1210 can be a conventional compact disk read-only memory (CD-ROM) or digital video disk read-only memory (DVD-ROM) or a rewriteable medium such as a CD-R, CD-RW, DVD−R, DVD−RW, DVD+R, DVD+RW, or DVD-RAM or a magneto-optical disk which is optically readable and magneto-optically rewriteable. Medium 1210 preferably has a suitable substrate 1211, which may be conventional, and a suitable coating 1212, which may be conventional, usually on one or both sides of substrate 1211.


In the case of a CD-based or DVD-based medium, as is well known, coating 1212 is reflective and is impressed with a plurality of pits 1213, arranged on one or more layers, to encode the machine-executable program. The arrangement of pits is read by reflecting laser light off the surface of coating 1212. A protective coating 1214, which preferably is substantially transparent, is provided on top of coating 1212.


In the case of magneto-optical disk, as is well known, coating 1212 has no pits 1213, but has a plurality of magnetic domains whose polarity or orientation can be changed magnetically when heated above a certain temperature, as by a laser (not shown). The orientation of the domains can be read by measuring the polarization of laser light reflected from coating 1212. The arrangement of the domains encodes the program as described above.


A PLD 140 programmed according to the present invention may be used in many kinds of electronic devices. One possible use is in a data processing system 1400 shown in FIG. 13. Data processing system 1400 may include one or more of the following components: a processor 1401; memory 1402; I/O circuitry 1403; and peripheral devices 1404. These components are coupled together by a system bus 1405 and are populated on a circuit board 1406 which is contained in an end-user system 1407.


System 1400 can be used in a wide variety of applications, such as computer networking, data networking, instrumentation, video processing, digital signal processing, or any other application where the advantage of using programmable or reprogrammable logic is desirable. PLD 140 can be used to perform a variety of different logic functions. For example, PLD 140 can be configured as a processor or controller that works in cooperation with processor 1401. PLD 140 may also be used as an arbiter for arbitrating access to a shared resources in system 1400. In yet another example, PLD 140 can be configured as an interface between processor 1401 and one of the other components in system 1400. It should be noted that system 1400 is only exemplary, and that the true scope and spirit of the invention should be indicated by the following claims.


Various technologies can be used to implement PLDs 140 as described above and incorporating this invention.


It will be understood that the foregoing is only illustrative of the principles of the invention, and that various modifications can be made by those skilled in the art without departing from the scope and spirit of the invention. For example, the various elements of this invention can be provided on a PLD in any desired number and/or arrangement. One skilled in the art will appreciate that the present invention can be practiced by other than the described embodiments, which are presented for purposes of illustration and not of limitation, and the present invention is limited only by the claims that follow.

Claims
  • 1. Circuitry for computing a first trigonometric function of an original input value, said circuitry comprising: circuitry for deriving an alternate input value from said original input value;circuitry for selecting a trigonometric input value from among candidate values including said original input value and said alternate input value, said circuitry for selecting selecting said alternate input value when said original input value is less than a threshold;circuitry for determining respective initial values of a plurality of respective trigonometric functions of said trigonometric input value; andcircuitry for deriving, based at least in part on a trigonometric identity involving said original input value and said alternate input value, a final value of said first trigonometric function of said original input value from said respective initial values of said plurality of respective trigonometric functions of said trigonometric input value.
  • 2. The circuitry of claim 1 wherein: said circuitry for determining respective initial values of a plurality of respective trigonometric functions determines sine and cosine values of said trigonometric input value; andsaid circuitry for deriving a final value selects said initial value of one of said plurality of respective trigonometric functions when said original input value is in a first range, and selects said initial value of another of said plurality of respective trigonometric functions when said original input value is in a second range.
  • 3. The circuitry of claim 2 wherein said circuitry for determining comprises CORDIC circuitry.
  • 4. The circuitry of claim 2 wherein: said circuitry for deriving an alternate input value subtracts said original input value from π/2 to generate said alternate input value;said first range includes values less than π/4; andsaid second range includes values at least equal to π/4.
  • 5. The circuitry of claim 2 wherein: said alternate input value comprises first and second alternate input values;said circuitry for deriving an alternate input value subtracts said original input value from π/4 to generate said first alternate input value, and subtracts π/4 from said original input value to generate said second alternate input value;said first range includes values at most equal to π/8;said second range includes values at least equal to 3π/8 and at most equal to π/2; andsaid circuitry for deriving a final value selectively combines sine and cosine of said first and second alternate input values.
  • 6. The circuitry of claim 1 wherein: said circuitry for determining respective initial values of a plurality of respective trigonometric functions determines sine and cosine values; andsaid circuitry for deriving a final value combines said respective initial values of each of said plurality of respective trigonometric functions in a first manner of combination when said input is in a first range, and combines said respective initial values of each of said plurality of respective trigonometric functions in a second manner of combination when said input is in a second range.
  • 7. The circuitry of claim 6 wherein said first manner of combination and said second manner of combination are selected from the group consisting of sums, differences, products, sums of products, differences of products, and combinations thereof.
  • 8. The circuitry of claim 7 wherein: said circuitry for deriving a final value is configured in a specialized processing block of a programmable integrated circuit device; andsaid specialized processing block comprises a plurality of multipliers and at least one adder.
  • 9. A method of configuring a programmable integrated circuit device as circuitry for computing a first trigonometric function of an original input value, said method comprising: configuring logic of said programmable integrated circuit device as circuitry for deriving an alternate input value from said original input value;configuring logic of said programmable integrated circuit device as circuitry for selecting a trigonometric input value from among candidate values including said original input value and said alternate input value, said circuitry for selecting selecting said alternate input value when said original input value is less than a threshold;configuring logic of said programmable integrated circuit device as circuitry for determining respective initial values of a plurality of respective trigonometric functions of said trigonometric input value; andconfiguring logic of said programmable integrated circuit device as circuitry for deriving, based at least in part on a trigonometric identity involving said original input value and said alternate input value, a final value of said first trigonometric function of said original input value from said respective initial values of said plurality of respective trigonometric functions of said alternate input value.
  • 10. The method of claim 9 wherein: configuring logic of said programmable integrated circuit device as circuitry for determining respective initial values of a plurality of respective trigonometric functions comprises configuring logic of said programmable integrated circuit device to determine sine and cosine values of said trigonometric input value; andsaid configuring logic of said programmable integrated circuit device as circuitry for deriving, based at least in part on a trigonometric identity, a final value of said first trigonometric function from said respective initial values of said plurality of respective trigonometric functions comprises configuring logic of said programmable integrated circuit device to select said initial value of one of said plurality of respective trigonometric functions when said original input value is in a first range, and to select said initial value of another of said plurality of respective trigonometric functions when said original input value is in a second range.
  • 11. The method of claim 10 wherein said configuring logic of said programmable integrated circuit device as circuitry for determining comprises configuring logic of said programmable integrated circuit device as CORDIC circuitry.
  • 12. The method of claim 10 wherein: said configuring logic of said programmable integrated circuit device as circuitry for deriving an alternate input value comprises configuring logic of said programmable integrated circuit device to subtract said original input value from π/2 to generate said alternate input value;said first range includes values less than π/4; andsaid second range includes values at least equal to π/4.
  • 13. The method of claim 10 wherein: said alternate input value comprises first and second alternate input values;said configuring logic of said programmable integrated circuit device as circuitry for deriving an alternate input value comprises configuring logic of said programmable integrated circuit device to subtract said original input value from π/4 to generate said first alternate input value, and to subtract π/4 from said original input value to generate said second alternate input value;said first range includes values at most equal to π/8;said second range includes values at least equal to 3π/8 and at most equal to π/2; andsaid configuring logic of said programmable integrated circuit device as circuitry for deriving a final value comprises configuring logic of said programmable integrated circuit device to selectively combine sine and cosine of said first and second alternate input values.
  • 14. The method of claim 9 wherein: said configuring logic of said programmable integrated circuit device as circuitry for determining respective initial values of a plurality of respective trigonometric functions comprises configuring logic of said programmable integrated circuit device as circuitry for determining sine and cosine values; andsaid configuring logic of said programmable integrated circuit device as circuitry for deriving a final value comprises configuring logic of said programmable integrated circuit device as circuitry for combining said respective initial values of each of said plurality of respective trigonometric functions in a first manner of combination when said original input value is in a first range, and for combining said respective initial values of each of said plurality of respective trigonometric functions in a second manner of combination when said original input value is in a second range.
  • 15. The method of claim 14 wherein said first manner of combination and said second manner of combination are selected from the group consisting of sums, differences, products, sums of products, differences of products, and combinations thereof.
  • 16. The method of claim 15 wherein said configuring logic of said programmable integrated circuit device as circuitry for deriving a final value comprises configuring said circuitry for deriving a final value in a specialized processing block of a programmable integrated circuit device, said specialized processing block comprising a plurality of multipliers and at least one adder.
  • 17. A non-transitory machine-readable data storage medium encoded with non-transitory machine-executable instructions for configuring a programmable integrated circuit device as circuitry for computing a trigonometric function of an original input value, said instructions comprising: instructions to configure logic of said programmable integrated circuit device as circuitry for deriving an alternate input value from said original input value;instructions to configure logic of said programmable integrated circuit device as circuitry for selecting a trigonometric input value from among candidate values including said original input value and said alternate input value, said circuitry for selecting selecting said alternate input value when said original input value is less than a threshold;instructions to configure logic of said programmable integrated circuit device as circuitry for determining respective initial values of a plurality of respective trigonometric functions of said trigonometric input value; andinstructions to configure logic of said programmable integrated circuit device as circuitry for deriving, based at least in part on a trigonometric identity involving said original input value and said alternate input value, a final value of said first trigonometric function of said original input value from said respective initial values of said plurality of respective trigonometric functions of said alternate input value.
  • 18. The non-transitory machine-readable data storage medium of claim 17 wherein: said instructions to configure logic of said programmable integrated circuit device as circuitry for determining respective initial values of a plurality of respective trigonometric functions comprise said instructions to configure logic of said programmable integrated circuit device to determine sine and cosine values; andsaid instructions to configure logic of said programmable integrated circuit device as circuitry for deriving, based at least in part on a trigonometric identity, a final value of said first trigonometric function from said respective initial values of said plurality of respective trigonometric functions comprise instructions to configure logic of said programmable integrated circuit device to select said initial value of one of said plurality of respective trigonometric functions when said original input value is in a first range, and to select said initial value of another of said plurality of respective trigonometric functions when said original input value is in a second range.
  • 19. The non-transitory machine-readable data storage medium of claim 18 wherein said instructions to configure logic of said programmable integrated circuit device as circuitry for determining comprise instructions to configure logic of said programmable integrated circuit device as CORDIC circuitry.
  • 20. The non-transitory machine-readable data storage medium of claim 18 wherein: said instructions to configure logic of said programmable integrated circuit device as circuitry for deriving an alternate input value comprise instructions to configure logic of said programmable integrated circuit device to subtract said original input value from π/2 to generate said alternate input value;said first range includes values at most equal to π/4; andsaid second range includes values at least equal to π/4.
  • 21. The non-transitory machine-readable data storage medium of claim 18 wherein: said alternate input value comprises first and second alternate input values;said instructions to configure logic of said programmable integrated circuit device as circuitry for deriving an alternate input value comprise instructions to configure logic of said programmable integrated circuit device to subtract said original input value from π/4 to generate said first alternate input value, and to subtract π/4 from said original input value to generate said second alternate input value;said first range includes values at most equal to π/8;said second range includes values at least equal to 3π/8 and at most equal to π/2; andsaid instructions to configure logic of said programmable integrated circuit device as circuitry for deriving a final value comprise instructions to configure logic of said programmable integrated circuit device to selectively combine sine and cosine of said first and second alternate input values.
  • 22. The non-transitory machine-readable data storage medium of claim 17 wherein: said instructions to configure logic of said programmable integrated circuit device as circuitry for determining respective initial values of a plurality of respective trigonometric functions comprise instructions to configure logic of said programmable integrated circuit device as circuitry for determining sine and cosine values; andsaid instructions to configure logic of said programmable integrated circuit device as circuitry for deriving a final value comprise instructions to configure logic of said programmable integrated circuit device as circuitry for combining said initial values of each of said plurality of respective trigonometric functions in a first manner of combination when said original input value is in a first range, and for combining said initial values of each of said plurality of respective trigonometric functions in a second manner of combination when said original input value is in a second range.
  • 23. The non-transitory machine-readable data storage medium of claim 18 wherein said first manner of combination and said second manner of combination are selected from the group consisting of sums, differences, products, sums of products, differences of products, and combinations thereof.
  • 24. The non-transitory machine-readable data storage medium of claim 23 wherein said instructions to configure logic of said programmable integrated circuit device as circuitry for deriving a final value comprise instructions to configure said circuitry for deriving a final value in a specialized processing block of a programmable integrated circuit device, said specialized processing block comprising a plurality of multipliers and at least one adder.
US Referenced Citations (333)
Number Name Date Kind
3473160 Wahlstrom Oct 1969 A
3896299 Rhodes Jul 1975 A
4156927 McElroy et al. May 1979 A
4179746 Tubbs Dec 1979 A
4212076 Conners Jul 1980 A
4215406 Gomola et al. Jul 1980 A
4215407 Gomola et al. Jul 1980 A
4422155 Amir et al. Dec 1983 A
4484259 Palmer et al. Nov 1984 A
4521907 Amir et al. Jun 1985 A
4575812 Kloker et al. Mar 1986 A
4597053 Chamberlin Jun 1986 A
4616330 Betz Oct 1986 A
4623961 Mackiewicz Nov 1986 A
4682302 Williams Jul 1987 A
4718057 Venkitakrishnan et al. Jan 1988 A
4727508 Williams Feb 1988 A
4736335 Barkan Apr 1988 A
4791590 Ku et al. Dec 1988 A
4799004 Mori Jan 1989 A
4823295 Mader Apr 1989 A
4839847 Laprade Jun 1989 A
4871930 Wong et al. Oct 1989 A
4912345 Steele et al. Mar 1990 A
4918637 Morton Apr 1990 A
4967160 Quievy et al. Oct 1990 A
4982354 Takeuchi et al. Jan 1991 A
4991010 Hailey et al. Feb 1991 A
4994997 Martin et al. Feb 1991 A
5073863 Zhang Dec 1991 A
5081604 Tanaka Jan 1992 A
5122685 Chan et al. Jun 1992 A
5128559 Steele Jul 1992 A
5175702 Beraud et al. Dec 1992 A
5208491 Ebeling et al. May 1993 A
RE34363 Freeman Aug 1993 E
5267187 Hsieh et al. Nov 1993 A
5296759 Sutherland et al. Mar 1994 A
5338983 Agarwala Aug 1994 A
5339263 White Aug 1994 A
5349250 New Sep 1994 A
5357152 Jennings, III et al. Oct 1994 A
5371422 Patel et al. Dec 1994 A
5375079 Uramoto et al. Dec 1994 A
5381357 Wedgwood et al. Jan 1995 A
5404324 Colon-Bonet Apr 1995 A
5424589 Dobbelaere et al. Jun 1995 A
5446651 Moyse et al. Aug 1995 A
5451948 Jekel Sep 1995 A
5452231 Butts et al. Sep 1995 A
5452375 Rousseau et al. Sep 1995 A
5457644 McCollum Oct 1995 A
5465226 Goto Nov 1995 A
5465375 Thepaut et al. Nov 1995 A
5483178 Costello et al. Jan 1996 A
5497498 Taylor Mar 1996 A
5500812 Saishi et al. Mar 1996 A
5500828 Doddington et al. Mar 1996 A
5523963 Hsieh et al. Jun 1996 A
5528550 Pawate et al. Jun 1996 A
5537601 Kimura et al. Jul 1996 A
5541864 Van Bavel et al. Jul 1996 A
5546018 New et al. Aug 1996 A
5550993 Ehlig et al. Aug 1996 A
5559450 Ngai et al. Sep 1996 A
5563526 Hastings et al. Oct 1996 A
5563819 Nelson Oct 1996 A
5570039 Oswald et al. Oct 1996 A
5570040 Lytle et al. Oct 1996 A
5572148 Lytle et al. Nov 1996 A
5581501 Sansbury et al. Dec 1996 A
5590350 Guttag et al. Dec 1996 A
5594366 Khong et al. Jan 1997 A
5594912 Brueckmann et al. Jan 1997 A
5596763 Guttag et al. Jan 1997 A
5606266 Pedersen Feb 1997 A
5617058 Adrian et al. Apr 1997 A
5631848 Laczko et al. May 1997 A
5633601 Nagaraj May 1997 A
5636150 Okamoto Jun 1997 A
5636368 Harrison et al. Jun 1997 A
5640578 Balmer et al. Jun 1997 A
5644519 Yatim et al. Jul 1997 A
5644522 Moyse et al. Jul 1997 A
5646545 Trimberger et al. Jul 1997 A
5646875 Taborn et al. Jul 1997 A
5648732 Duncan Jul 1997 A
5652903 Weng et al. Jul 1997 A
5655069 Ogawara et al. Aug 1997 A
5664192 Lloyd et al. Sep 1997 A
5689195 Cliff et al. Nov 1997 A
5696708 Leung Dec 1997 A
5729495 Madurawe Mar 1998 A
5740404 Baji Apr 1998 A
5744980 McGowan et al. Apr 1998 A
5744991 Jefferson et al. Apr 1998 A
5754459 Telikepalli May 1998 A
5761483 Trimberger Jun 1998 A
5764555 McPherson et al. Jun 1998 A
5768613 Asghar Jun 1998 A
5771186 Kodali et al. Jun 1998 A
5777912 Leung et al. Jul 1998 A
5784636 Rupp Jul 1998 A
5790446 Yu et al. Aug 1998 A
5794067 Kadowaki Aug 1998 A
5801546 Pierce et al. Sep 1998 A
5805477 Perner Sep 1998 A
5805913 Guttag et al. Sep 1998 A
5808926 Gorshtein et al. Sep 1998 A
5812479 Cliff et al. Sep 1998 A
5812562 Baeg Sep 1998 A
5815422 Dockser Sep 1998 A
5821776 McGowan Oct 1998 A
5825202 Tavana et al. Oct 1998 A
5838165 Chatter Nov 1998 A
5841684 Dockser Nov 1998 A
5847579 Trimberger Dec 1998 A
5847978 Ogura et al. Dec 1998 A
5847981 Kelley et al. Dec 1998 A
5859878 Phillips et al. Jan 1999 A
5869979 Bocchino Feb 1999 A
5872380 Rostoker et al. Feb 1999 A
5874834 New Feb 1999 A
5878250 LeBlanc Mar 1999 A
5880981 Kojima et al. Mar 1999 A
5892962 Cloutier Apr 1999 A
5894228 Reddy et al. Apr 1999 A
5898602 Rothman et al. Apr 1999 A
5931898 Khoury Aug 1999 A
5942914 Reddy et al. Aug 1999 A
5944774 Dent Aug 1999 A
5949710 Pass et al. Sep 1999 A
5951673 Miyata Sep 1999 A
5956265 Lewis Sep 1999 A
5959871 Pierzchala et al. Sep 1999 A
5960193 Guttag et al. Sep 1999 A
5961635 Guttag et al. Oct 1999 A
5963048 Harrison et al. Oct 1999 A
5963050 Young et al. Oct 1999 A
5968196 Ramamurthy et al. Oct 1999 A
5970254 Cooke et al. Oct 1999 A
5978260 Trimberger et al. Nov 1999 A
5982195 Cliff et al. Nov 1999 A
5986465 Mendel Nov 1999 A
5991788 Mintzer Nov 1999 A
5991898 Rajski et al. Nov 1999 A
5995748 Guttag et al. Nov 1999 A
5999015 Cliff et al. Dec 1999 A
5999990 Sharrit et al. Dec 1999 A
6005806 Madurawe et al. Dec 1999 A
6006321 Abbott Dec 1999 A
6009451 Burns Dec 1999 A
6018755 Gonikberg et al. Jan 2000 A
6020759 Heile Feb 2000 A
6021423 Nag et al. Feb 2000 A
6029187 Verbauwhede Feb 2000 A
6031763 Sansbury Feb 2000 A
6041339 Yu et al. Mar 2000 A
6041340 Mintzer Mar 2000 A
6052327 Reddy et al. Apr 2000 A
6052755 Terrill et al. Apr 2000 A
6055555 Boswell et al. Apr 2000 A
6064614 Khoury May 2000 A
6065131 Andrews et al. May 2000 A
6066960 Pedersen May 2000 A
6069487 Lane et al. May 2000 A
6072994 Phillips et al. Jun 2000 A
6073154 Dick Jun 2000 A
6075381 LaBerge Jun 2000 A
6084429 Trimberger Jul 2000 A
6085317 Smith Jul 2000 A
6091261 DeLange Jul 2000 A
6091765 Pietzold, III et al. Jul 2000 A
6094726 Gonion et al. Jul 2000 A
6097988 Tobias Aug 2000 A
6098163 Guttag et al. Aug 2000 A
6107820 Jefferson et al. Aug 2000 A
6107821 Kelem et al. Aug 2000 A
6107824 Reddy et al. Aug 2000 A
6130554 Kolze et al. Oct 2000 A
6140839 Kaviani et al. Oct 2000 A
6144980 Oberman Nov 2000 A
6154049 New Nov 2000 A
6157210 Zaveri et al. Dec 2000 A
6163788 Chen et al. Dec 2000 A
6167415 Fischer et al. Dec 2000 A
6175849 Smith Jan 2001 B1
6215326 Jefferson et al. Apr 2001 B1
6226735 Mirsky May 2001 B1
6242947 Trimberger Jun 2001 B1
6243729 Staszewski Jun 2001 B1
6246258 Lesea Jun 2001 B1
6260053 Maulik et al. Jul 2001 B1
6279021 Takano et al. Aug 2001 B1
6286024 Yano et al. Sep 2001 B1
6314442 Suzuki Nov 2001 B1
6314551 Borland Nov 2001 B1
6321246 Page et al. Nov 2001 B1
6323680 Pedersen et al. Nov 2001 B1
6327605 Arakawa et al. Dec 2001 B2
6351142 Abbott Feb 2002 B1
6353843 Chehrazi et al. Mar 2002 B1
6359468 Park et al. Mar 2002 B1
6360240 Takano et al. Mar 2002 B1
6362650 New et al. Mar 2002 B1
6366944 Hossain et al. Apr 2002 B1
6367003 Davis Apr 2002 B1
6369610 Cheung et al. Apr 2002 B1
6377970 Abdallah et al. Apr 2002 B1
6385632 Choe et al. May 2002 B1
6407576 Ngai et al. Jun 2002 B1
6407694 Cox et al. Jun 2002 B1
6427157 Webb Jul 2002 B1
6434587 Liao et al. Aug 2002 B1
6438569 Abbott Aug 2002 B1
6438570 Miller Aug 2002 B1
6446107 Knowles Sep 2002 B1
6453382 Heile Sep 2002 B1
6467017 Ngai et al. Oct 2002 B1
6480980 Koe Nov 2002 B2
6483343 Faith et al. Nov 2002 B1
6487575 Oberman Nov 2002 B1
6523055 Yu et al. Feb 2003 B1
6523057 Savo et al. Feb 2003 B1
6531888 Abbott Mar 2003 B2
6538470 Langhammer et al. Mar 2003 B1
6542000 Black et al. Apr 2003 B1
6556044 Langhammer et al. Apr 2003 B2
6557092 Callen Apr 2003 B1
6571268 Giacalone et al. May 2003 B1
6573749 New et al. Jun 2003 B2
6574762 Karimi et al. Jun 2003 B1
6591283 Conway et al. Jul 2003 B1
6591357 Mirsky Jul 2003 B2
6600495 Boland et al. Jul 2003 B1
6600788 Dick et al. Jul 2003 B1
6628140 Langhammer et al. Sep 2003 B2
6687722 Larsson et al. Feb 2004 B1
6692534 Wang et al. Feb 2004 B1
6700581 Baldwin et al. Mar 2004 B2
6725441 Keller et al. Apr 2004 B1
6728901 Rajski et al. Apr 2004 B1
6731133 Feng et al. May 2004 B1
6732134 Rosenberg et al. May 2004 B1
6744278 Liu et al. Jun 2004 B1
6745254 Boggs et al. Jun 2004 B2
6763367 Kwon et al. Jul 2004 B2
6771094 Langhammer et al. Aug 2004 B1
6774669 Liu et al. Aug 2004 B1
6781408 Langhammer Aug 2004 B1
6781410 Pani et al. Aug 2004 B2
6788104 Singh et al. Sep 2004 B2
6801924 Green et al. Oct 2004 B1
6836839 Master et al. Dec 2004 B2
6874079 Hogenauer Mar 2005 B2
6889238 Johnson May 2005 B2
6904471 Boggs et al. Jun 2005 B2
6924663 Masui et al. Aug 2005 B2
6963890 Dutta et al. Nov 2005 B2
6971083 Farrugia et al. Nov 2005 B1
6978287 Langhammer Dec 2005 B1
6983300 Ferroussat Jan 2006 B2
7020673 Ozawa Mar 2006 B2
7047272 Giacalone et al. May 2006 B2
7062526 Hoyle Jun 2006 B1
7093204 Oktem et al. Aug 2006 B2
7107305 Deng et al. Sep 2006 B2
7113969 Green et al. Sep 2006 B1
7181484 Stribaek et al. Feb 2007 B2
7313585 Winterrowd Dec 2007 B2
7395298 Debes et al. Jul 2008 B2
7401109 Koc et al. Jul 2008 B2
7409417 Lou Aug 2008 B2
7415542 Hennedy et al. Aug 2008 B2
7421465 Rarick et al. Sep 2008 B1
7428565 Fujimori Sep 2008 B2
7428566 Siu et al. Sep 2008 B2
7430578 Debes et al. Sep 2008 B2
7430656 Sperber et al. Sep 2008 B2
7447310 Koc et al. Nov 2008 B2
7472155 Simkins et al. Dec 2008 B2
7508936 Eberle et al. Mar 2009 B2
7536430 Guevokian et al. May 2009 B2
7567997 Simkins et al. Jul 2009 B2
7590676 Langhammer Sep 2009 B1
7646430 Brown Elliott et al. Jan 2010 B2
7668896 Lutz et al. Feb 2010 B2
7719446 Rosenthal et al. May 2010 B2
7769797 Cho et al. Aug 2010 B2
7930335 Gura Apr 2011 B2
7930336 Langhammer Apr 2011 B2
20010023425 Oberman et al. Sep 2001 A1
20010029515 Mirsky Oct 2001 A1
20010037352 Hong Nov 2001 A1
20020002573 Landers et al. Jan 2002 A1
20020038324 Page et al. Mar 2002 A1
20020049798 Wang et al. Apr 2002 A1
20020078114 Wang et al. Jun 2002 A1
20020089348 Langhammer Jul 2002 A1
20020116434 Nancekievill Aug 2002 A1
20020129073 Page et al. Sep 2002 A1
20030088757 Lindner et al. May 2003 A1
20040064770 Xin Apr 2004 A1
20040083412 Corbin et al. Apr 2004 A1
20040103133 Gurney May 2004 A1
20040122882 Zakharov et al. Jun 2004 A1
20040148321 Guevorkian et al. Jul 2004 A1
20040172439 Lin Sep 2004 A1
20040178818 Crotty et al. Sep 2004 A1
20040193981 Clark et al. Sep 2004 A1
20040267857 Abel et al. Dec 2004 A1
20040267863 Bhushan et al. Dec 2004 A1
20050038842 Stoye Feb 2005 A1
20050144212 Simkins et al. Jun 2005 A1
20050144215 Simkins et al. Jun 2005 A1
20050144216 Simkins et al. Jun 2005 A1
20050166038 Wang et al. Jul 2005 A1
20050187997 Zheng et al. Aug 2005 A1
20050187999 Zheng et al. Aug 2005 A1
20050262175 Iino et al. Nov 2005 A1
20060020655 Lin Jan 2006 A1
20060059215 Maharatna et al. Mar 2006 A1
20070083585 St. Denis et al. Apr 2007 A1
20070124352 Wittig May 2007 A1
20070185951 Lee et al. Aug 2007 A1
20070185952 Langhammer et al. Aug 2007 A1
20070241773 Hutchings et al. Oct 2007 A1
20080133627 Langhammer et al. Jun 2008 A1
20080183783 Tubbs Jul 2008 A1
20090172052 DeLaquil et al. Jul 2009 A1
20090187615 Abe et al. Jul 2009 A1
20090300088 Michaels et al. Dec 2009 A1
20100098189 Oketani Apr 2010 A1
Foreign Referenced Citations (45)
Number Date Country
0 158 430 Oct 1985 EP
0 380 456 Aug 1990 EP
0 411 491 Feb 1991 EP
0 461 798 Dec 1991 EP
0 498 066 Aug 1992 EP
0 555 092 Aug 1993 EP
0 606 653 Jul 1994 EP
0 657 803 Jun 1995 EP
0 660 227 Jun 1995 EP
0 668 659 Aug 1995 EP
0 721 159 Jul 1996 EP
0 905 906 Mar 1999 EP
0 909 028 Apr 1999 EP
0 927 393 Jul 1999 EP
0 992 885 Apr 2000 EP
1 031 934 Aug 2000 EP
1 058 185 Dec 2000 EP
1 220 108 Jul 2002 EP
2 283 602 May 1995 GB
2 286 737 Aug 1995 GB
2 318 198 Apr 1998 GB
61-237133 Oct 1986 JP
63-216131 Aug 1988 JP
4-332036 Nov 1992 JP
5-134851 Jun 1993 JP
06-187129 Jul 1994 JP
7-135447 May 1995 JP
11-296345 Oct 1999 JP
2000-259394 Sep 2000 JP
2002-108606 Apr 2002 JP
2002-251281 Sep 2002 JP
WO95-27243 Oct 1995 WO
WO96-28774 Sep 1996 WO
WO97-08606 Mar 1997 WO
WO98-12629 Mar 1998 WO
WO98-32071 Jul 1998 WO
WO98-38741 Sep 1998 WO
WO99-22292 May 1999 WO
WO99-31574 Jun 1999 WO
WO99-56394 Nov 1999 WO
WO00-51239 Aug 2000 WO
WO00-52824 Sep 2000 WO
WO01-13562 Feb 2001 WO
WO 2005066832 Jul 2005 WO
WO2005-101190 Oct 2005 WO
Non-Patent Literature Citations (75)
Entry
Altera Corporation, “Advanced Synthesis Cookbook: A Design Guide for Stratix II, Stratix III and Stratix IV Devices,” Document Version 3.0, 112 pgs., May 2008.
deDinechin, F. et al., “Large multipliers with less DSP blocks,” retrieved from http://hal-ens-lyon.archives-ouvertes.fr/ensl-00356421/en/, 9 pgs., available online Jan. 2009.
Wajih, E.-H.Y. et al., “Efficient Hardware Architecture of Recursive Karatsuba-Ofman Multiplier,” 3rd International Conference on Design and Technology of Integrated Systems in Nanoscale Era, 6 pgs., Mar. 2008.
Zhou, G. et al., “Efficient and High-Throughput Implementations of AES-GCM on FPGAs,” International Conference on Field-Programmable Technology, 8 pgs., Dec. 2007.
Altera Corporation, “Stratix II Device Handbook, Chapter 6—DSP Blocks in Stratix II Devices,” v1.1, Jul. 2004.
Altera Corporation, “Digital Signal Processing (DSP),” Stratix Device Handbook, vol. 2, Chapter 6 and Chapter 7, v1.1 (Sep. 2004).
Altera Corporation, “DSP Blocks in Stratix II and Stratix II GX Devices,” Stratix II Device Handbook, vol. 2, Chapter 6, v4.0 (Oct. 2005).
Amos, D., “PLD architectures match DSP algorithms,” Electronic Product Design, vol. 17, No. 7, Jul. 1996, pp. 30, 32.
Analog Devices, Inc., The Applications Engineering Staff of Analog Devices, DSP Division, Digital Signal Processing Applications Using the ADSP-2100 Family (edited by Amy Mar), 1990, pp. 141-192).
Andrejas, J., et al., “Reusable DSP functions in FPGAs,” Field-Programmable Logic and Applications. Roadmap to Reconfigurable Computing. 10th International Conference, FPL 2000. Proceedings (Lecture Notes in Computer Science vol. 1896), Aug. 27-30, 2000, pp. 456-461.
Aoki, T., “Signed-weight arithmetic and its application to a field-programmable digital filter architecture,” IEICE Transactions on Electronics , 1999 , vol. E82C, No. 9, Sep. 1999, pp. 1687-1698.
Ashour, M.A., et al., “An FPGA implementation guide for some different types of serial-parallel multipler-structures,” Microelectronics Journal , vol. 31, No. 3, 2000, pp. 161-168.
Berg, B.L., et al.“Designing Power and Area Efficient Multistage FIR Decimators with Economical Low Order Filters,” ChipCenter Technical Note, Dec. 2001.
Bursky, D., “Programmable Logic Challenges Traditional ASIC SoC Designs”, Electronic Design, Apr. 15, 2002.
Chhabra, A. et al., Texas Instruments Inc., “A Block Floating Point Implementation on the TMS320C54x DSP”, Application Report SPRA610, Dec. 1999, pp. 1-10.
Colet, p., “When DSPs and FPGAs meet: Optimizing image processing architectures,” Advanced Imaging, vol. 12, No. 9, Sep. 1997, pp. 14, 16, 18.
Crookes, D., et al., “Design and implementation of a high level programming environment for FPGA-based image processing,” IEE Proceedings-Vision, Image and Signal Processing, vol. 147, No. 4, Aug. 2000, pp. 377-384.
Debowski, L., et al., “A new flexible architecture of digital control systems based on DSP and complex CPLD technology for power conversion applications,” PCIM 2000: Europe Official Proceedings of the Thirty-Seventh International Intelligent Motion Conference, Jun. 6-8, 2000, pp. 281-286.
Dick, C., et al., “Configurable logic for digital communications: some signal processing perspectives,” IEEE Communications Magazine, vol. 37, No. 8, Aug. 1999, pp. 107-111.
Do, T.-T., et al., “A flexible implementation of high-performance FIR filters on Xilinx FPGAs,” Field-Programmable Logic and Applications: From FPGAs to Computing Paradigm. 8th International Workshop, FPL'98. Proceedings, Hartenstein, R.W., et al., eds., Aug. 31-Sep. 3, 1998, pp. 441-445.
Gaffer, A.A., et al., “Floating-Point Bitwidth Analysis via Automatic Differentiation,” IEEE Conference on Field Programmable Technology, Hong Kong, Dec. 2002.
Guccione, S.A.,“Run-time Reconfiguration at Xilinx,” Parallel and distributed processing: 15 IPDPS 2000 workshops, Rolim, J., ed., May 1-5, 2000, p. 873.
Hauck, S., “The Future of Reconfigurable Systems,” Keynote Address, 5th Canadian Conference on Field Programmable Devices, Jun. 1998, http:--www.ee.washington.edu-people-faculty-hauck-publications-ReconfigFuture.PDF.
Heysters, P.M., et al., “Mapping of DSP algorithms on field programmable function arrays,” Field-Programmable Logic and Applications. Roadmap to Reconfigurable Computing. 10th International Conference, FPL 2000. Proceedings (Lecture Notes in Computer Science vol. 1896) Aug. 27-30, 2000, pp. 400-411.
Huang, J., et al., “Simulated Performance of 1000BASE-T Receiver with Different Analog Front End Designs,” Proceedings of the 35th Asilomar Conference on Signals, Systems, and Computers, Nov. 4-7, 2001.
Lattice Semiconductor Corp, ORCA® FPGA Express™ Interface Manual:.ispLEVER® Version 3.0, 2002.
Lucent Technologies, Microelectronics Group,“Implementing and Optimizing Multipliers in ORCA™ FPGAs,”, Application Note.AP97-008FGPA, Feb. 1997.
“Implementing Multipliers in FLEX 10K EABs”, Altera, Mar. 1996.
“Implementing Logic with the Embedded Array in FLEX 10K Devices”, Altera, May 2001, ver. 2.1.
Jinghua Li, “Design a pocket multi-bit multiplier in FPGA,” 1996 2nd International Conference on ASIC Proceedings (IEEE Cat. No. 96TH8140) Oct. 21-24, 1996, pp. 275-279.
Jones, G., “Field-programmable digital signal conditioning,” Electronic Product Design, vol. 21, No. 6, Jun. 2000, pp. C36-C38.
Kiefer, R., et al., “Performance comparison of software-FPGA hardware partitions for a DSP application,” 14th Australian Microelectronics Conference. Microelectronics: Technology Today for the Future. MICRO '97 Proceedings, Sep. 28-Oct. 1, 1997, pp. 88-93.
Kramberger, I., “DSP acceleration using a reconfigurable FPGA,” ISIE '99. Proceedings of the IEEE International Symposium on Industrial Electronics (Cat. No. 99TH8465), vol. 3 , Jul. 12-16, 1999, pp. 1522-1525.
Langhammer, M., “How to implement DSP in programmable logic,” Elettronica Oggi, No. 266 , Dec. 1998, pp. 113-115.
Langhammer, M., “Implementing a DSP in Programmable Logic,” Online EE Times, May 1998, http:--www.eetimes.com-editorial-1998-coverstory9805.html.
Lazaravich, B.V., “Function block oriented field programmable logic arrays,” Motorola, Inc. Technical Developments, vol. 18, Mar. 1993, pp. 10-11.
Lund, D., et al., “A new development system for reconfigurable digital signal processing,” First International Conference on 3G Mobile Communication Technologies (Conf. Publ. No. 471), Mar. 27-29, 2000, pp. 306-310.
Miller, N.L., et al., “Reconfigurable integrated circuit for high performance computer arithmetic,” Proceedings of the 1998 IEE Colloquium on Evolvable Hardware Systems (Digest), No. 233, 1998, pp. 2-1-2-4.
Mintzer, L., “Xilinx FPGA as an FFT processor,” Electronic Engineering, vol. 69, No. 845, May 1997, pp. 81, 82, 84.
Faura et al., “A Novel Mixed Signal Programmable Device With On-Chip Microprocessor,” Custom Integrated Circuits Conference, 1997. Proceedings of the IEEE 1997 Santa Clara, CA, USA, May 5, 1997, pp. 103-106.
Nozal, L., et al., “A new vision system: programmable logic devices and digital signal processor architecture (PLD+DSP),” Proceedings IECON '91. 1991 International Conference on Industrial Electronics, Control and Instrumentation (Cat. No. 91CH2976-9), vol. 3, Oct. 28-Nov. 1, 1991, pp. 2014-2018.
Papenfuss, J.R, et al., “Implementation of a real-time, frequency selective, RF channel simulator using a hybrid DSP-FPGA architecture,” RAWCON 2000: 2000 IEEE Radio and Wireless Conference (Cat. No. 00EX404), Sep. 10-13, 2000, pp. 135-138.
Parhami, B., “Configurable arithmetic arrays with data-driven control,” 34th Asilomar Conference on Signals, Systems and Computers, vol. 1, 2000, pp. 89-93.
“The QuickDSP Design Guide”, Quicklogic, Aug. 2001, revision B.
“QuickDSP™ Family Data Sheet”, Quicklogic, Aug. 7, 2001, revision B.
Rangasayee, K., “Complex PLDs let you produce efficient arithmetic designs,” EDN (European Edition), vol. 41, No. 13, Jun. 20, 1996, pp. 109, 110, 112, 114, 116.
Rosado, A., et al., “A high-speed multiplier coprocessor unit based on FPGA,” Journal of Electrical Engineering, vol. 48, No. 11-12, 1997, pp. 298-302.
Santillan-Q., G.F., et al., “Real-time integer convolution implemented using systolic arrays and a digit-serial architecture in complex programmable logic devices,” Proceedings of the Third International Workshop on Design of Mixed-Mode Integrated Circuits and Applications (Cat. No. 99EX303), Jul. 26-28, 1999, pp. 147-150.
Texas Instruments Inc., “TMS320C54x DSP Reference Set, vol. 1: CPU and Peripherals”, Literature No. SPRU131F, Apr. 1999, pp. 2-1 through 2-16 and 4-1 through 4-29.
Tisserand, A., et al., “An on-line arithmetic based FPGA for low power custom computing,” Field Programmable Logic and Applications, 9th International Workshop, FPL'99, Proceedings (Lecture Notes in Computer Science vol. 1673), Lysaght, P., et al., eds., Aug. 30-Sep. 1, 1999, pp. 264-273.
Tralka, C., “Symbiosis of DSP and PLD,” Elektronik, vol. 49, No. 14 , Jul. 11, 2000, pp. 84-96.
Underwood, K. “FPGAs vs. CPUs: Trends in Peak Floating-Point Performance,” Proceedings of the 2004 ACM-SIGDA 12th International Symposium on Field Programmable Gate Arrays, pp. 171-180, Feb. 22-24, 2004.
Valls, J., et al., “A Study About FPGA-Based Digital Filters,” Signal Processing Systems, 1998, SIPS 98, 1998 IEEE Workshop, Oct. 10, 1998, pp. 192-201.
“Virtex-II 1.5V Field-Programmable Gate Arrays”, Xilinx, Jan. 25, 2001, module 2 of 4.
“Virtex-II 1.5V Field-Programmable Gate Arrays”, Xilinx, Apr. 2, 2001, module 1 of 4.
“Virtex-II 1.5V Field-Programmable Gate Arrays”, Xilinx, Apr. 2, 2001, module 2 of 4.
Walters, A.L., “A Scaleable FIR Filter Implementation Using 32-bit Floating-Point Complex Arithmetic on ,a FPGA Based Custom Computing Platform,” Allison L. Walters, Thesis Submitted to the Faculty of Virginia Polytechnic Institute and State University, Jan. 30, 1998.
Weisstein, E.W., “Karatsuba Multiplication,” MathWorld—A Wolfram Web Resource (Dec. 9, 2007), accessed Dec. 11, 2007 at http:--mathworld.wolfram.com-KaratsubaMultiplication.html.
Wenzel, L., “Field programmable gate arrays (FPGAs) to replace digital signal processor integrated circuits,” Elektronik , vol. 49, No. 5, Mar. 7, 2000, pp. 78-86.
“Xilinx Unveils New FPGA Architecture to Enable High-Performance, 10 Million System Gate Designs”, Xilinx, Jun. 22, 2000.
“Xilinx Announces DSP Algorithms, Tools and Features for Virtex-II Architecture”, Xilinx, Nov. 21, 2000.
Xilinx Inc., “Virtex-II 1.5V Field-Programmable Gate Arrays”, Advance Product Specification, DS031-2 (v1.9), Nov. 29, 2001, Module 2 of 4, pp. 1-39.
Xilinx Inc., “Using Embedded Multipliers”, Virtex-II Platform FPGA Handbook, UG002 (v1.3), Dec. 3, 2001, pp. 251-257.
Xilinx, Inc., “A 1D Systolic FIR,” copyright 1994-2002, downloaded from http:--www.iro.umontreal.ca-˜aboulham-F6221-Xilinx%20A%201D%20systolic%20FIR.htm.
Xilinx, Inc., “The Future of FPGA's,” White Paper, available Nov. 14, 2005 for download from http:--www.xilinx.com-prs—rls,5yrwhite.htm.
Xilinx Inc., “XtremeDSP Design Considerations User Guide,” v 1.2, Feb. 4, 2005.
Xilinx Inc., “Complex Multiplier v2.0”, DS291 Product Specification/Datasheet, Nov. 2004.
Haynes, S.D., et al., “Configurable multiplier blocks for embedding in FPGAs,” Electronics Letters, vol. 34, No. 7, pp. 638-639 (Apr. 2, 1998).
Kim, Y., et al., “Fast GPU Implementation for the Solution of Tridiagonal Matrix Systems,” Journal of Korean Institute of Information Scientists and Engineers, vol. 32, No. 12, pp. 692-704, Dec. 2005.
Govindu, G. et al., “A Library of Parameterizable Floating-Point Cores for FPGAs and Their Application to Scientific Computing,” Proc Int'l Conf. Eng. Reconfigurable Systems and Algorithms (ERSA'05), Jun. 2005.
Govindu, G. et al., “Analysis of High-performance Floating-point Arithmetic on FPGAs,” Proceedings of the 18th International Parallel and Distributed Processing Symposium (PDPS'04), pp. 149-156, Apr. 2004.
Nakasato, N., et al., “Acceleration of Hydrosynamical Simulations using a FPGA board”, The Institute of Electronics Information and Communication Technical Report CPSY2005-47, vol. 105, No. 515, Jan. 17, 2006.
Osana, Y., et al., “Hardware-resource Utilization Analysis on an FPGA-Based Biochemical Simulator ReCSiP”, The Institute of Electronics Information and Communication Technical Report CPSY2005-63, vol. 105, No. 516, Jan. 18, 2006.
Vladimirova, T. et al., “Floating-Point Mathematical Co-Processor for a Single-Chip On-Board Computer,” MAPLD'03 Conference, D5, Sep. 2003.
Altera Corporation, “FIR Compiler: MegaCore® Function User Guide,” version 3.3.0, rev. 1, pp. 3 11 through 3 15 (Oct. 2005).
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