Configuring floating point operations in a programmable device

Information

  • Patent Grant
  • 8650231
  • Patent Number
    8,650,231
  • Date Filed
    Wednesday, November 25, 2009
    16 years ago
  • Date Issued
    Tuesday, February 11, 2014
    11 years ago
Abstract
A programmable device is programmed to perform arithmetic operations in an internal format that, unlike known standard formats that store numbers in normalized form and require normalization after each computational step, stores numbers in unnormalized form and does not require normalization after each step. Numbers are converted into unnormalized form at the beginning of an operation and converted back to normalized form at the end of the operation. If necessary to avoid data loss, a number may be normalized after an intermediate step. To conserve resources, rather than configuring the every intermediate operation to have the same mantissa size, in the internal format the mantissa size may start out smaller and grow after each operation.
Description
BACKGROUND OF THE INVENTION

This invention relates to performing floating point arithmetic operations in programmable devices, such as programmable logic devices (PLDs), including the use of specialized processing blocks, which may be included in such devices, to perform floating point operations.


As applications for which PLDs are used increase in complexity, it has become more common to design PLDs to include specialized processing blocks in addition to blocks of generic programmable logic resources. Such specialized processing blocks may include a concentration of circuitry on a PLD that has been partly or fully hardwired to perform one or more specific tasks, such as a logical or a mathematical operation. A specialized processing block may also contain one or more specialized structures, such as an array of configurable memory elements. Examples of structures that are commonly implemented in such specialized processing blocks include: multipliers, arithmetic logic units (ALUs), barrel-shifters, various memory elements (such as FIFO/LIFO/SIPO/RAM/ROM/CAM blocks and register files), AND/NAND/OR/NOR arrays, etc., or combinations thereof.


One particularly useful type of specialized processing block that has been provided on PLDs is a digital signal processing (DSP) block, which may be used to process, e.g., audio signals. Such blocks are frequently also referred to as multiply-accumulate (“MAC”) blocks, because they include structures to perform multiplication operations, and sums and/or accumulations of multiplication operations.


For example, PLDs sold by Altera Corporation, of San Jose, Calif., under the family name STRATIX® includes DSP blocks, each of which includes a plurality of multipliers (e.g., four 18-bit-by-18-bit multipliers). Each of those DSP blocks also includes adders and registers, as well as programmable connectors (e.g., multiplexers) that allow the various components to be configured in different ways. In each such block, the multipliers can be configured not only as individual multipliers, but also as four smaller multipliers, or as one larger multiplier (e.g., one 36-bit-by-36-bit multiplier in the case of four 18-bit-by-18-bit multipliers). In addition, e.g., one complex multiplication (which decomposes into two multiplication operations for each of the real and imaginary parts) can be performed. In order to support four 18-bit-by-18-bit multiplication operations, a block in a member of the aforementioned STRATIX® device family may have 4×(18+18)=144 inputs. Similarly, the output of an 18-bit-by-18-bit multiplication is 36 bits wide, so to support the output of four such multiplication operations, such a block would have 36×4=144 outputs.


The arithmetic operations to be performed by a PLD frequently are floating point operations. However, to the extent that known PLDs, with or without DSP blocks or other specialized blocks or structures, including the aforementioned STRATIX® family of PLDs, can perform floating point operations at all, they operate in accordance with the IEEE754-1985 standard, which requires that values be normalized at all times because it implies a leading “1”. However, that leads to certain inefficiencies as described below.


SUMMARY OF THE INVENTION

The present invention relates to programmable devices having improved floating point operation capabilities. In particular, the present invention carries out floating point operations without normalization, although the results may be normalized if IEEE754-1985 compliance is required. In addition, normalization may be performed in intermediate steps if loss of data might otherwise result.


Therefore, in accordance with the present invention, there is provided a method of configuring a programmable device to perform floating point operations on input values formatted in accordance with a standard requiring a first mantissa size and a first exponent size. The method includes configuring logic of the programmable device to reformat the input values to have an initial mantissa size different from the first mantissa size. Logic of said programmable device also is configured to perform a tree of successive operations to compute a final result. Each respective operation in a first level of the tree of successive operations has a first number of the reformatted input values as inputs and provides a respective first intermediate result having a mantissa size increased by at least one bit left of its binal point as compared to the initial mantissa size. Each operation in a respective successive level of the tree of successive operations after the first level of said tree of successive operations, other than a final level, has the first number of inputs and provides a respective intermediate result and the final level provides the final result. Each of the respective intermediate results and the final result is unnormalized and has a mantissa size increased by at least one bit left of its binal point as compared to an intermediate result on an immediately preceding level. Logic of the programmable device also is configured to reformat the result in accordance with the standard to the first mantissa size.


A programmable device so configured, and a machine-readable data storage medium encoded with software for performing the method, are also provided.





BRIEF DESCRIPTION OF THE DRAWINGS

The above and other objects and advantages of the invention 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 is a schematic representation of conversion of numbers according to the IEEE754-1985 standard format to a preferred embodiment of a format according to the present invention;



FIG. 2 is a schematic representation of conversion of numbers according to a preferred embodiment of a format according to the present invention to the IEEE754-1985 standard format;



FIG. 3 is a schematic representation of the configuration of a simple addition in accordance with the invention;



FIG. 4 is a schematic representation of the configuration of a somewhat more complicated addition in accordance with the invention;



FIG. 5 is a schematic representation of the configuration of a preferred embodiment of an arithmetic logic unit in accordance with the invention;



FIG. 6 is a schematic representation of the configuration of a preferred embodiment of a multiplier in accordance with the invention;



FIG. 7 is a schematic representation of an addition operation illustrating another embodiment of the invention;



FIG. 8 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. 9 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. 10 is a simplified block diagram of an illustrative system employing a programmable device incorporating the present invention.





DETAILED DESCRIPTION OF THE INVENTION

Floating point numbers are commonplace for representing real numbers in scientific notation in computing systems. Examples of real numbers in scientific notation are:

    • 3.1415926510×100 (π)
    • 2.71828182810×100 (e)
    • 0.00000000110 or 1.010×10−9 (seconds in a nanosecond)
    • 315576000010 or 3.1557610×109 (seconds in a century)


The first two examples are real numbers in the range of the lower integers, the third example represents a very small fraction, and the fourth example represents a very large integer. Floating point numbers in computing systems are designed to cover the large numeric range and diverse precision requirements shown in these examples. Fixed point number systems have a very limited window of representation which prevents them from representing very large or very small numbers simultaneously. The position of the notional binary-point in fixed point numbers addresses this numeric range problem to a certain extent but does so at the expense of precision. With a floating point number the window of representation can move, which allows the appropriate amount of precision for the scale of the number.


Floating point representation is generally preferred over fixed point representation in computing systems because it permits an ideal balance of numeric range and precision. However, floating point representation requires more complex implementation compared to fixed point representation.


The IEEE754-1985 standard is commonly used for floating point numbers. A floating point number includes three different parts: the sign of the number, its mantissa and its exponent. Each of these parts may be represented by a binary number and, in the IEEE754-1985 format, have the following bit sizes:

















Sign
Exponent
Bias
Mantissa



















Single
1 bit
 8 bits
−127
23 bits


Precision
[31]
[30 . . . 23]

[22 . . . 00]


32-Bit






Double
1 bit
11 bits
−1023
52 bits


Precision
[63]
[62 . . . 52]

[51 . . . 0] 


64-Bit









The exponent preferably is an unsigned binary number which, for the single precision format, ranges from 0 to 255. In order to represent a very small number, it is necessary to use negative exponents. To achieve this the exponent preferably has a negative bias associated with it. For single-precision numbers, the bias preferably is −127. For example a value of 140 for the exponent actually represents (140-127)=13, and a value of 100 represents (100-127)=−27. For double precision numbers, the exponent bias preferably is −1023.


As discussed above, according to the standard, the mantissa is a normalized number—i.e., it has no leading zeroes and represents the precision component of a floating point number. Because the mantissa is stored in binary format, the leading bit can either be a 0 or a 1, but for a normalized number it will always be a 1. Therefore, in a system where numbers are always normalized, the leading bit need not be stored and can be implied, effectively giving the mantissa one extra bit of precision. Therefore, in single precision format, the mantissa typically includes 24 bits of precision.


However, the IEEE754-1985 standard requires continuous normalization—i.e., normalization after every step of a multistep computation—to maintain the leading “1” to preserve accuracy. This is expensive in terms of PLD resources, as each normalization operation requires two steps—(1) finding the position of the “1”, and (2) shifting the fractional part to get a leading “1” (which is then eliminated, because it is implied).


In accordance with the invention, there is no implied leading “1”, so that normalization is not required. Although this requires that one bit of precision be given up, because all bits must be kept, rather than implied, this greatly reduces the required logic, particularly shifting logic, and therefore the latency of the floating point operations. Moreover, in a PLD that already has dedicated arithmetic circuits, such as multipliers and/or adders, that are capable of handling the extra bits, there is no additional cost in terms of logic resources to handle those extra bits.


Preferably, the floating point representation in accordance with the invention uses a signed fractional component, with greater precision. Some operations may be configured in general-purpose logic of the programmable logic device. However, multiplication, at least, is more efficiently performed in a dedicated multiplier such as may be available in the aforementioned DSP block. The extra precision in accordance with the invention requires large multipliers, which heretofore have consumed more resources than the shifting logic required for normalization. However, in the aforementioned STRATIX® II PLDs, as well as those described in copending, commonly-assigned U.S. patent application Ser. Nos. 11/447,329, 11/447,370, 11/447,472 and 11/447,474, all filed Jun. 5, 2006, 11/426,403, filed Jun. 26, 2006, and 11/458,361, filed Jul. 18, 2006, each of which is hereby incorporated herein in its respective entirety, large dedicated multipliers are available, and are more efficient than shifting logic. This allows the efficient use of a signed fractional component.


Specifically, according to a preferred method according to the invention for configuring a programmable logic device to perform floating point operations, the programmable logic device preferably is configured so that floating point values in accordance with a first format, such as the IEEE754-1985 standard format, preferably are converted to an internal format for calculation purposes, and are reconverted to the standard format upon completion of the operations.


Whereas the IEEE754-1985 standard format includes a 24-bit unsigned mantissa (23 bits plus the implied “1”) and an 8-bit exponent, the internal format according to the invention preferably includes a 32-bit signed mantissa and a 10-bit exponent. When converting from the standard 24-bit format to the 32-bit format of the invention, the implied leading “1” of the mantissa is made explicit and preferably is initially positioned at the 28th bit location. This leaves the four most significant bits of the 32-bit number available for overflows as operations progress. For example, 16 additions could be performed before any overflow would consume all four bits. Similarly, because the original standard representation is only 24 bits wide, the four least significant bits also are available for any underflows that may occur.


If this method is implemented on the aforementioned STRATIX® II PLD, or on a PLD of any of the above-incorporated patent applications, which include DSP blocks capable of 36-bit multiplications, then the multiplications of the 32-bit mantissas can be accomplished within the 36-bit dedicated multipliers, making the multipliers more efficient. Moreover, the mantissa size could be expanded to 36 bits if necessary or desired. However, the invention could be implemented even where no dedicated multipliers are available, using programmed general-purpose logic. Moreover, if dedicated multipliers are available, but are only large enough for IEEE754-1985-compliant operations, computations other than multiplications could be performed in programmed general-purpose logic, with the multiplications being performed in the dedicated multipliers. In such a case, the values would have to be renormalized before each multiplication step, but would not have to be normalized for other steps either before or after a multiplication step, except at the end of the operation.


As stated above, preferably, and ordinarily, during floating point operations in accordance with the invention, the operands remain in the format according to the invention, and are converted back to their original format only upon completion of operations. Because of the initial presence of the leading and trailing bits, as well as the larger exponent size, during operations it is possible to continue beyond conditions that might have led to overflows or underflows in the original format, because of the possibility that the accumulation of further results may reverse the overflow or underflow condition.


However, if during operation the accumulation of underflows or overflows reaches the point that information may be lost—e.g., there would be an overflow if the data were converted back to the standard format, or an underflow would be approached such that fewer than three significant bits beyond the required mantissa precision (i.e., in this example, fewer than 1+23+3=27 bits) would remain—it may be desirable in accordance with the invention to normalize the data at an intermediate step to prevent lost of precision. In such a case, subsequent operations preferably would not include further normalization until the final result is achieved (unless a condition again arises in which data may be lost).


Alternatively, if overflow or underflow is likely (e.g., there will be many operations in a calculation), then the start position of the mantissa can be changed from the 28th bit position to another position (to the right to prevent overflows; to the left to prevent underflows). The correct result can be maintained by adjusting the exponents accordingly. The larger exponent size (10 bits instead of 8 bits) allows room for the necessary exponent adjustments.


The examples that follow illustrate configurations, in accordance with the invention, of a programmable logic device to perform a number of different arithmetic operations. For simplicity, these examples do not show pipelining between stages, nor do they show circuitry for handling special cases, such as zero, infinity or not-a-number (NAN) situations.


The examples include conversions in both directions between the format of the IEEE754-1985 standard and the internal format according to a preferred embodiment of this invention. Preferred embodiments of those conversions are illustrated in FIGS. 1 and 2.



FIG. 1 shows a preferred embodiment of the conversion 10 from a value represented in the IEEE754-1985 standard format 11 to the same value represented, in the embodiment described above, in the format 12 according to the present invention. As seen, in format 11, the value is indicated by three numbers representing the sign 110, the mantissa 111 and the exponent 112. As indicated above, sign 110 is one bit wide, mantissa 111 is 23 bits wide but represents 24 bits of precision because it has an implied leading “1”, and exponent 112 is eight bits wide. In format 12, there is no separate number representing the sign, while signed mantissa 120 is 32 bits wide and exponent 121 is ten bits wide.


As shown in FIG. 1, exponent 112 converts directly to exponent 121 by the addition of two leading zeroes, as clearly the value of the exponent cannot change. The availability of two extra bits, however, provides for greater ranging of the value during internal computations, prior to conversion back to the IEEE754-1985 standard. This helps reduce the occurrence of overflows and underflows.


Sign bit 110 and 23-bit-wide mantissa 111 (carrying 24 bits of precision) convert to four sign bits 122 and 24-bit mantissa portion 123 with the aid of exclusive-OR (XOR) 124. Four trailing bits 125 (because again the value cannot change in the conversion) are added to provide 32-bit mantissa 120. The trailing bits are zeroes for positive numbers, and ones for negative numbers (which are inverted).


The operation of XOR 124 preferably is as follows:


If sign bit 110 is a “0”, then XOR 124 has no effect. If sign bit 110 is a “1” (signifying a negative number), then XOR 124 inverts the mantissa—i.e., it converts the mantissa to a one's-complement number. The actual computation requires a two's-complement number. The one's-complement number can be converted to a two's-complement number by adding a “1” to the least significant bit of the one's-complement number. An adder can be provided as part of each conversion 10. However, such adders are very large, and because the precision of the mantissa in the format according to the present invention is greater than that of the IEEE754-1985 mantissa, it is also possible to omit this addition completely without significantly affecting the result.


As a third alternative, a single adder can be provided after a group of conversions 10, which adds to the result a number equal to the total number of negative numbers within that group of conversions 10. For example, if in an addition of eight numbers (meaning there are eight conversions), five of those numbers are negative, the value 510 (1012) can be added to the one's-complement result to give the two's-complement result. This becomes more complicated in the case of multiplications, but can still be used where there is a local cluster of operations.



FIG. 2 shows the conversion 20 from a value represented in the format 12 according to the present invention to the same value represented in the IEEE754-1985 standard format 11. As seen, in block 21, the absolute value of mantissa 120 is taken, because the mantissa is signed in the format according to the invention, but unsigned in the IEEE784-1985 format. After that, the conversion operates similarly to the conversion under the IEEE754-1985 standard. Thus, in block 22 the number of leading zeroes is counted to find the implied leading “1”. The mantissa is then left-shifted in block 23 by the number found in block 22. Any necessary rounding is performed in block 24. To convert exponent 121, an offset adjustment is subtracted from the exponent by subtractor 25 to account for the position of the implied leading “1” during the original conversion 10 to the format according to the invention. The offset adjustment typically is 410 (1002) a shown, but if the mantissa size or position of the leading “1” on conversion changes, the offset adjustment to the exponent would change as well to compensate.


In FIGS. 3-6, “IF” (internal format) refers to a preferred embodiment (as described above) of the format according to the present invention, while “IEEE754” refers to the format according to the IEEE754-1985 standard.



FIG. 3 shows a simple case 30 of configuring logic to add two floating point numbers a and b to obtain their floating point sum c. In this case 30, a first block 31 of logic preferably is configured from programmable logic to convert a from the IEEE754-1985 standard format to the internal format, and a second block 32 of logic preferably is configured from programmable logic to convert b from the IEEE754-1985 standard format to the internal format. Blocks 31 and 32 preferably are substantially identical. An arithmetic logic unit (ALU) 33 preferably is configured from programmable logic to add the values of a and b in the internal format. A block 34 preferably is configured to convert the result c back to IEEE754-1985 standard format from the internal format.


ALU 33, operating in the internal format, is simpler than a corresponding ALU operating in the IEEE754-1985 standard format because it does not have include the shifting logic needed to deal with the implied leading “1” and therefore is about half the size of a standard-format ALU. However, conversion 34 adds about the same amount of logic as ALU 33, while conversions 31, 32 add a negligible amount of logic. Therefore, in this simple example of adding two numbers, the net result is approximately the same under either format in terms of circuit size and latency, because one standard-format ALU is replaced with two blocks each about half the size of the standard-format ALU.



FIG. 4 shows the more complex case 40 of adding together four numbers a, b, c and d. In this case 40, blocks 41-44 of logic preferably are configured from programmable logic to respectively convert a, b, c and d from the IEEE754-1985 standard format to the internal format. A first arithmetic logic unit (ALU) 45 preferably is configured from programmable logic to add the values of a and b in the internal format. ALU 46 similarly may be configured from programmable logic to add c and d in the internal format. ALU 47, also similarly configured from programmable logic may be provided to add the intermediate sums from ALU 45 and ALU 46. Block 34 preferably is configured from programmable logic to convert the result e back to IEEE754-1985 standard format from the internal format.


As in case 30, each of conversions 41-44 adds negligible logic, while each of ALUs 45-47, as well as conversion 34, adds half the logic of a standard-format ALU. Using the standard format, the operation of case 40 could have been performed with three standard-format ALUs, while in case 40, it is performed with four blocks (three ALUs 45-47 and conversion 34) approximating in total the size of two standard-format ALUs. Thus, the circuit is about two-thirds the size using the format according to the invention as compared to the standard format.



FIG. 5 shows a preferred embodiment of the configuration of an ALU 50 for addition using the format according to the invention, which may be used as ALU 33, 45, 46 or 47. ALU 50 is similar to the first portion of a standard-format ALU. However, there is no normalization after the addition, which is where the size savings occurs. The two exponents 51, 52 are compared at 53, and the result is used to control multiplexers 54, 55 to right-shift the mantissa 56, 57 of the smaller number. Depending on the signs of the inputs and the ADDSUB control signal 58, none, one, or both of the numbers are one's-complemented at 59, then added at 500. The larger of the two input exponents 51, 52 is the resultant exponent 501. In a preferred embodiment, ALU 50 may be configured from programmable logic, but alternatively some of the components, such as adder 500, may be provided as dedicated circuitry.



FIG. 6 shows a preferred embodiment of the configuration of a multiplier 60 for multiplication using the format according to the invention. Multiplier 60 is similar to the first portion of a standard-format multiplier. Multiplication circuitry 61 may be configured from programmable logic but preferably may be provided as dedicated circuitry as described above. As in the addition case, there is no normalization after the multiplication, resulting in size savings as compared to a standard-format multiplication. However, for multiplication, the normalization range is more limited—typically only one bit instead of 23 bits—so the savings are smaller. Small additional savings result from the elimination of the need for rounding, which is required in the standard format.


According to another aspect of the invention, instead of having a fixed internal format, with a fixed mantissa size, the mantissa size is adjusted for each step of a calculation. A normalized mantissa represents a magnitude of between 1.010 and 1.999 . . . 9910 at some given exponent. The number with the smaller exponent is has its mantissa (including the leading “1”) right shifted by the difference between the two exponents. If the exponents are the same, then there is no shift. As a consequence, for two-input operations, the largest unnormalized mantissa at any node can be 3.99999, while the smallest can be 0 (the subtraction of two equal numbers). 3.999 . . . 999 in binary 11.11111 . . . 1112. If two of these unnormalized numbers were added, the maximum result would be 7.9999 . . . 999910, represented in binary as 111.111 . . . 1112. A tree of 16 numbers would have a maximum value of 31.999 . . . 99910, or 11111.111 . . . 1112. In signed magnitude format, there will be an additional bit to represent the sign.


Thus, for a multi-level addition using a binary tree (i.e., a tree of two-input adders), the mantissa size at the first, input, level is set according to the expected input values. At each level, the number of bits at the most-significant end—i.e., to the left of the “binal” point (the binary equivalent of a decimal point, separating places signifying values less than 1 from places signifying values greater than or equal to 1)—is increased by 1. Starting with a normalized input, with one bit to the left of the binal point (or two bits if there is a sign bit), at the first level and performing the first-level additions, the number of bits in the second-level input to the left of the binal point if there is no further normalization would be two (or three if there is a sign bit). After the second-level additions, there would be three (or four) bits to the left of the binal point in the third-level inputs. At the inputs to the nth level, then, the number of bits of wordgrowth as compared to the inputs to first level (n=1), is n−1.


For multi-input adders, the number of bits of wordgrowth at each level may be greater. Generally, if the “base,” or number of inputs per adder, is m, then when m is a power of 2, the number of bits of wordgrowth per level is m/2. However, if the base is not a power of 2, the number of bits of wordgrowth will be irregular (although on average it may be m/2). For example, if using four-input adders (a “quaternary” tree), the number of bits of wordgrowth would be 2 per level.


However, if using, e.g., three-input adders (a “ternary” tree), the number of bits of wordgrowth would be 2 per level in some cases and 1 per level in other cases. Specifically, a three-input adder has three inputs, each of which may have a maximum value of 1.999910. Therefore, the output of each first level adder has a maximum value of 3×1.999910=5.999910 which requires 3 bits to the left of the binal point in binary representation, or 2 bits of growth over the input level. At the next level, the inputs have a maximum value of 5.999910, so with three inputs the maximum output value would be 3×5.999910=17.999910, which requires 5 bits to the left of the binal point in binary representation, or again 2 bits of growth over the previous level. At the level after that, the inputs have a maximum value of 17.999910, so with three inputs the maximum output value would be 3×17.999910=53.999910, which requires 6 bits to the left of the binal point in binary representation, or in this case only 1 bit of growth over the previous level.


To generalize, then, for a base m, the number of bits at the nth level would be ceil(log2(mn)), meaning that the wordgrowth to the left of the binal point at the nth level, as compared to the (n−1)st level, is ceil(log2(mn)−ceil(log2(mn-1). And for an n-level tree of adders having a total of M inputs, regardless of base, the total wordgrowth to the left of the binal point over the entire tree would be ceil(log2M)−1.


Taking the example of binary tree 700 shown in FIG. 7, where there are three inputs 711 in the first level 710, two inputs 712 are added at 714 to yield a result 721 in the second level 720, and the third input 713 is given a “bye” to the second level 720 where it is added at 724 to result 721 to yield result 731 in third level 730. Here, M=3.


In that example, each input 711 has two bits (including one sign bit) to the left of the binal point 740, second level result 721 has three bits to the left of the binal point 740, and third-level result 731 has four bits to the left of the binal point 740, for an increase, for the tree as a whole, of two bits, over the number of bits in the input level. This is expected, insofar as ceil(log2(3))=ceil(1.585)=2.


The foregoing increases in mantissa size to the left of the binal point prevent overflow. On the other hand, increases in mantissa size to the right of the binal point are generally more flexible, based on the user's tolerance for underflow (i.e., tolerance for loss of data as values become so small that they underflow to zero because of insufficient mantissa size to the right of the binal point) or the user's tolerance for bit cancellation (i.e., the loss of data when numbers very close to one another are subtracted). Although underflow could be handled using a “sticky bit” as is common in IEEE754 applications, growth in mantissa size to the right of the binal point might preserve lost data resulting from underflow or bit cancellation. According to this aspect of the invention, because it is a matter of user tolerance, growth in mantissa size to the right of the binal point may be less deterministic than growth to the left of the binal point.


Specifically, any growth 750 to the right of the binal point may be arbitrary as determined by the user, or may be subject to heuristic rules. For example, one bit may be added to the right of the binal point for every n bits added to left of the binal point, optionally subject to a maximum number of added bits.


This aspect of the invention can be implemented with both signed numbers and signed magnitude numbers. The use of signed numbers will make the individual adder/subtractor nodes smaller, and have a lower latency, because a potentially negative number in the fixed-point addition/subtraction portion of the operation will not have to be converted to a positive number and sign bit. If signed numbers are used, more processing may be required to convert between signed magnitude and signed number formats, as well as for some internal functions such as negation or absolute values. However, a common application of this aspect of the invention for large floating point datapaths will likely be dot or inner products, so use of negation or absolute value functions should be infrequent.


As before, the results of any calculation not formatted according to the foregoing standard will be renormalized to meet the standard when necessary to output a value in accordance with the standard, or at intermediate points as discussed above. However, because the mantissa size at each level or step of each calculation need not be the same according to this aspect of the invention, implementation of any user design can be expected to save up to about 15% of resources as compared to the initial aspect of the invention discussed above. For example, to add 16 numbers, a tree of 15 adders may be used. If a 32-bit result is needed and all adders are 32 bits wide, then 15×32=480 resource units are needed. However, according to this aspect of the invention, assuming wordgrowth of two bits per node (e.g., one bit on each side of the binal point), the number of resource units needed might be 8×26=208 plus 4×28=112 plus 2×30=60 plus 1×32=32 for a total of 412 resource units, which is just under 86% of 480 resource units, for a savings of over 14%.


Although in the foregoing discussion, the only standard referred to is the IEEE754-1985 standard, it should be noted the invention applies regardless of what the standard is, and moreover the output standard may not be the same as the input standard. Moreover, any reference herein, or in the claims that follow, to “input,” “output,” “initial” or “final” may refer to an intermediate point at which renormalization is performed, as discussed above, rather than to an absolute input or output.


Instructions for carrying out a method according to this invention 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 to perform arithmetic operations in accordance with the format describe 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. 8 presents a cross section of a magnetic data storage medium 600 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 600 can be a floppy diskette or hard disk, or magnetic tape, having a suitable substrate 601, which may be conventional, and a suitable coating 602, 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 600 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 602 of medium 600 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. 9 shows a cross section of an optically-readable data storage medium 700 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 700 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 700 preferably has a suitable substrate 701, which may be conventional, and a suitable coating 702, which may be conventional, usually on one or both sides of substrate 701.


In the case of a CD-based or DVD-based medium, as is well known, coating 702 is reflective and is impressed with a plurality of pits 703, 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 702. A protective coating 704, which preferably is substantially transparent, is provided on top of coating 702.


In the case of magneto-optical disk, as is well known, coating 702 has no pits 703, 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 702. The arrangement of the domains encodes the program as described above.


Thus it is seen that a method for carrying out floating point operations, a programmable device programmed to perform the method, and software for carrying out the programming, have been provided.


A programmable device, such as a PLD 90, programmed according to the present invention may be used in many kinds of electronic devices. One possible use is in a data processing system 900 shown in FIG. 10. Data processing system 900 may include one or more of the following components: a processor 901; memory 902; I/O circuitry 903; and peripheral devices 904. These components are coupled together by a system bus 905 and are populated on a circuit board 906 which is contained in an end-user system 907.


System 900 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 90 can be used to perform a variety of different logic functions. For example, PLD 90 can be configured as a processor or controller that works in cooperation with processor 901. PLD 90 may also be used as an arbiter for arbitrating access to a shared resources in system 900. In yet another example, PLD 90 can be configured as an interface between processor 901 and one of the other components in system 900. It should be noted that system 900 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 programmable devices, such as PLDs 90, 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 programmable device 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. A method of configuring a programmable device to perform floating point operations on input values formatted in accordance with an input standard requiring a first mantissa size and a first exponent size, said method comprising: configuring logic of said programmable device to reformat said input values to have an initial mantissa size different from said first mantissa size;configuring logic of said programmable device to perform a tree of successive operations to compute a final result, wherein:each respective operation in a first level of said tree of successive operations has a first number of said reformatted input values as inputs and provides a respective first intermediate result having a mantissa size increased by at least one bit left of its binal point as compared to said initial mantissa size;each operation in a respective successive level of said tree of successive operations after said first level of said tree of successive operations, other than a final level, has said first number of inputs and provides a respective intermediate result and said final level provides said final result, andeach of said respective intermediate results and said final result is unnormalized and has a mantissa size increased by at least one bit left of its binal point as compared to an intermediate result on an immediately preceding level; andconfiguring logic of said programmable device to reformat said final result in accordance with an output standard.
  • 2. The method of claim 1 wherein: said output standard is said input standard; andsaid configuring logic of said programmable device to reformat said final result comprises configuring said logic of said programmable device to reformat said final result in accordance with said input standard to said first mantissa size.
  • 3. The method of claim 1 wherein each of said input values is in signed number format.
  • 4. The method of claim 1 wherein each of said input values is in signed magnitude format.
  • 5. The method of claim 1 wherein: said first number is m; andsaid at least one bit at a level n of said tree equals ceil(log2(mn)−ceil(log2(mn-1).
  • 6. The method of claim 1 wherein: said mantissa size of said final result is increased by a second number of bits left of its binal point as compared to said initial mantissa size; andsaid second number of bits is equal to ceil(log2M) where M is a total number of inputs entering said tree.
  • 7. The method of claim 1 wherein: at least one of said first intermediate result, said respective intermediate results and said final result has a mantissa size increased by one bit right of its binal point 5 as compared to said initial mantissa size.
  • 8. The method of claim 7 wherein: said first intermediate result has a mantissa size increased by one bit right of its binal point as compared to said initial mantissa size; andeach of said respective intermediate results and said final result has a mantissa size increased by one bit right of its binal point as compared to a previous intermediate result.
  • 9. The method of claim 7 wherein, whenever addition of a bit left of the binal point of a result of one of said operations results in the mantissa size of the result of that one of said operations exceeding the initial mantissa size to the left of the binal point by an integer multiple of a predetermined number of bits, and no previous one of said operations has resulted in the mantissa size exceeding the initial mantissa size to the left of the binal point by that integer multiple of the predetermined number of bits, the result of that one of said operations has its mantissa size increased by one bit right of its binal point as compared to an immediately preceding intermediate result.
  • 10. A programmable integrated circuit device configured to perform floating point operations on values formatted in accordance with an input standard requiring a first mantissa size and a first exponent size, said configured programmable integrated circuit device comprising: logic circuitry configured to reformat said input values to have an initial mantissa size different from said first mantissa size;logic circuitry configured to perform a tree of successive operations to compute a final result, wherein:each respective operation in a first level of said tree of successive operations has a first number of said reformatted input values as inputs and provides a respective first intermediate result having a mantissa size increased by at least one bit left of its binal point as compared to said initial mantissa size;each operation in a respective successive level of said tree of successive operations after said first level of said tree of successive operations, other than a final level, has said first number of inputs and provides a respective intermediate result and said final level provides said final result, andeach of said respective intermediate results and said final result is unnormalized and has a mantissa size increased by at least one bit left of its binal point as compared to an intermediate result on an immediately preceding level; andlogic circuitry configured to reformat said final result in accordance with said standard to said first mantissa size configuring logic of said programmable device to reformat said final result in accordance with an output standard.
  • 11. The configured programmable integrated circuit device of claim 10 wherein: said output standard is said input standard; andsaid logic circuitry configured to reformat said final result comprises logic configured to reformat said final result in accordance with said input standard to said first mantissa size.
  • 12. The configured programmable integrated circuit device of claim 10 wherein: said first number is m; andsaid at least one bit at a level n of said tree equals ceil(log2(mn)−ceil(log2(mn-1).
  • 13. The configured programmable integrated circuit device of claim 10 wherein: said mantissa size of said final result is increased by a second number of bits left of its binal point as compared to said initial mantissa size; andsaid second number of bits is equal to ceil(log2M) where M is a total number of inputs entering said tree.
  • 14. The configured programmable integrated circuit device of claim 10 wherein said logic circuitry is configured to increase the mantissa size of at least one of said first intermediate result, said respective intermediate results and said final result by at least one bit right of its binal point as compared to said initial mantissa size.
  • 15. The configured programmable integrated circuit device of claim 14 wherein: said first intermediate result has a mantissa size increased by at least one bit right of its binal point as compared to said initial mantissa size; andeach of said respective intermediate results and said final result has a mantissa size increased by one bit right of its binal point as compared to an immediately preceding intermediate result.
  • 16. The configured programmable integrated circuit device of claim 14 wherein, whenever addition of a bit left of the binal point of a result of one of said operations results in the mantissa size of the result of that one of said operations exceeding the initial mantissa size to the left of the binal point by an integer multiple of a predetermined number of bits, and no previous one of said operations has resulted in the mantissa size exceeding the initial mantissa size to the left of the binal point by that integer multiple of the predetermined number of bits, the result of that one of said operations has its mantissa size increased by one bit right of its binal point as compared to an immediately preceding intermediate result.
  • 17. A non-transistory machine-readable data storage medium encoded with machine-executable instructions for configuring a programmable device to execute a method of performing floating point operations on values formatted in accordance with an input standard requiring a first mantissa size and a first exponent size, said instructions comprising: instructions to configure logic of said programmable device to reformat said input values to have an initial mantissa size different from said first mantissa size;instructions to configure logic of said programmable device to perform a tree of successive operations to compute a final result, wherein:each respective operation in a first level of said tree of successive operations has a first number of said reformatted input values as inputs and provides a respective first intermediate result having a mantissa size increased by at least one bit left of its binal point as compared to said initial mantissa size;each operation in a respective successive level of said tree of successive operations after said first level of said tree of successive operations, other than a final level, has said number of inputs and provides a respective intermediate result and said final level provides said final result, andeach of said respective intermediate results and said final result is unnormalized and has a mantissa size increased by at least one bit left of its binal point as compared to an intermediate result on an immediately preceding level; andinstructions to configure logic of said programmable device to reformat said final result in accordance with an output standard.
  • 18. The non-transistory machine-readable data storage medium of claim 17 wherein: said output standard is said input standard; andinstructions to configure logic of said programmable device to reformat said final result comprise instructions to configure said logic of said programmable device to reformat said final result in accordance with said input standard to said first mantissa size.
  • 19. The non-transistory machine-readable data storage medium of claim 17 wherein: said first number is m; andsaid at least one bit at a level n of said tree equals ceil(log2(mn)−ceil(log2(mn-1).
  • 20. The non-transistory machine-readable data storage medium of claim 17 wherein: said mantissa size of said final result is increased by a second number of bits left of its binal point as compared to said initial mantissa size; andsaid second number of bits is equal to ceil(log2M) where M is a total number of inputs entering said tree.
  • 21. The non-transistory machine-readable data storage medium of claim 17 wherein said instructions configure said logic to increase the mantissa size of at least one of first intermediate result, said respective intermediate results and 5 said final result by one bit right of its binal point as compared to said initial mantissa size.
  • 22. The non-transistory machine-readable data storage medium of claim 21 wherein said instructions configure said logic to: increase said mantissa size of said first intermediate result by one bit right of its binal point as compared to said initial mantissa size; andincrease said mantissa size of each of said respective intermediate results and said final result by one bit right of its binal point as compared to a previous intermediate result.
  • 23. The non-transistory machine-readable data storage medium of claim 21 wherein said instructions configure said logic to, whenever addition of a bit left of the binal point of a result of one of said operations results in the mantissa size of the result of that one of said operations exceeding the initial mantissa size to the left of the binal point by an integer multiple of a predetermined number of bits, and no previous one of said operations has resulted in the mantissa size exceeding the initial mantissa size to the left of the binal point by that integer multiple of the predetermined number of bits, increase the mantissa size of the result of that one of said operations increased by one bit right of its binal point as compared to a previous intermediate result.
CROSS REFERENCE TO RELATED APPLICATION

This is a continuation-in-part of copending, commonly-assigned U.S. patent application Ser. No. 11/625,655, filed Jan. 22, 2007, which is hereby incorporated by reference herein in its entirety.

US Referenced Citations (363)
Number Name Date Kind
3473160 Wahlstrom Oct 1969 A
3697734 Booth et al. Oct 1972 A
3800130 Martinson et al. Mar 1974 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
4754421 Bosshart Jun 1988 A
4791590 Ku et al. Dec 1988 A
4799004 Mori Jan 1989 A
4823260 Imel et al. Apr 1989 A
4823295 Mader Apr 1989 A
4839847 Laprade Jun 1989 A
4871930 Wong et al. Oct 1989 A
4893268 Denman et al. Jan 1990 A
4908788 Fujiyama Mar 1990 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
4999803 Turrini et al. Mar 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
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
5373461 Bearden 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
6052773 DeHon 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 De Lange 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
6108772 Sharangpani 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
6346824 New Feb 2002 B1
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
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
6578060 Chen et al. Jun 2003 B2
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
6915322 Hong Jul 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
7024446 Langhammer et al. Apr 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
7230451 Langhammer Jun 2007 B1
7313585 Winterrowd Dec 2007 B2
7343388 Burney et al. Mar 2008 B1
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
7650374 Gura et al. Jan 2010 B1
7668896 Lutz et al. Feb 2010 B2
7719446 Rosenthal et al. May 2010 B2
7720898 Driker et al. May 2010 B2
7769797 Cho et al. Aug 2010 B2
7814136 Verma et al. Oct 2010 B1
7822799 Langhammer et al. Oct 2010 B1
7917567 Mason et al. Mar 2011 B1
7930335 Gura Apr 2011 B2
7930336 Langhammer Apr 2011 B2
8024394 Prokopenko Sep 2011 B2
8090758 Shimanek et al. Jan 2012 B1
8112466 Minz et al. Feb 2012 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
20020032713 Jou et al. Mar 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
20030065699 Burns Apr 2003 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
20060112160 Ishii et al. May 2006 A1
20070083585 St. Denis et al. Apr 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
20080159441 Liao et al. Jul 2008 A1
20080183783 Tubbs Jul 2008 A1
20090083358 Allen Mar 2009 A1
20090113186 Kato et al. Apr 2009 A1
20090172052 DeLaquil et al. Jul 2009 A1
20090182795 Dobbek et al. Jul 2009 A1
20090187615 Abe et al. Jul 2009 A1
20090228689 Muff et al. Sep 2009 A1
20090292750 Reyzin et al. Nov 2009 A1
20090300088 Michaels et al. Dec 2009 A1
20100098189 Oketani Apr 2010 A1
20100146022 Swartzlander et al. Jun 2010 A1
20100191939 Muff et al. Jul 2010 A1
20120166512 Wong et al. Jun 2012 A1
Foreign Referenced Citations (46)
Number Date Country
0 158 430 Oct 1985 EP
0 380 456 Aug 1990 EP
0 411 491 Feb 1991 EP
0 419 105 Mar 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
WO9527243 Oct 1995 WO
WO9628774 Sep 1996 WO
WO9708606 Mar 1997 WO
WO9812629 Mar 1998 WO
WO9832071 Jul 1998 WO
WO9838741 Sep 1998 WO
WO9922292 May 1999 WO
WO9931574 Jun 1999 WO
WO9956394 Nov 1999 WO
WO0051239 Aug 2000 WO
WO0052824 Sep 2000 WO
WO0113562 Feb 2001 WO
WO 2005066832 Jul 2005 WO
WO2005101190 Oct 2005 WO
Non-Patent Literature Citations (83)
Entry
Altera Corporation, “FIR Compiler: MegaCore® Function User Guide,” version 3.3.0, rev. 1, pp. 3 11 through 3 15 (Oct. 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.
Xilinx, Inc., “Implementing Barrel Shifters Using Multipliers,” p. 1-4, Aug. 17, 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).
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.
Xilinx Inc., “XtremeDSP Design Considerations User Guide,” v 1.2, Feb. 4, 2005.
Altera Corporation, “Digital Signal Processing (DSP),” Stratix Device Handbook, vol. 2, Chapter 6 and Chapter 7, v1.1 (Sep. 2004).
Fujioka, Y., et al., “240MOPS Reconfigurable Parallel VLSI Processor for Robot Control,” Proceedings of the 1992 International Conference on Industrial Electronics, Control, Instrumentation, and Automation: Signal Processing and Systems Control; Intelligent Sensors and Instrumentation, vol. 3, pp. 1385-1390, Nov. 9-13, 1992.
Altera Corporation, “Stratix II Device Handbook, Chapter 6—DSP Blocks in Stratix II Devices,” v1.1, Jul. 2004.
Xilinx Inc., “Complex Multiplier v2.0”, DS291 Product Specification/Datasheet, Nov. 2004.
Martinson, L. et al., “Digital Matched Filtering with Pipelined Floating Point Fast Fourier Transforms (FFT's),” IEEE Transactions on Acoustics, Speech, and Signal Processing, vol. ASSP-23, No. 2, pp. 222-234, Apr. 1975.
Haynes, S.D., et al., “Configurable multiplier blocks for embedding in FPGAs,” Electronics Letters, vol. 34, No. 7, pp. 638-639 (Apr. 2, 1998).
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 multiplier-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.
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.
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.
Altera, “DSP Blocks in Stratix III Devices”, Chapter 5, pp. 1-42, Mar. 2010.
Karlström, P., et al., “High Performance, Low Latency FPGA based Floating Point Adder and Multiplier Units in a Virtex 4,” Norchip Conf., pp. 31-34, 2006.
Thapliyal, H., et al., “Combined Integer and Floating Point Multiplication Architecture (CIFM) for FPGSs and Its Reversible Logic Implementation”, Proceedings MWSCAS 2006, Puerto Rico, 5 pages, Aug. 2006.
Thapliyal, H., et al., “Combined Integer and Variable Precision (CIVP) Floating Point Multiplication Architecture for FPGAs”, Proceedings of the 2007 International Conference on Parallel and Distributed Processing Techniques and Applications (PDPTA'07), Las Vegas, US, vol. 1, pp. 449-450, Jun. 2007.
Xilinx, Inc., “Virtex-5 ExtremeDSP Design Considerations,” User Guide UG193, v2.6, 114 pages, Oct. 2007.
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.
Continuation in Parts (1)
Number Date Country
Parent 11625655 Jan 2007 US
Child 12625800 US