Electrical computers: arithmetic processing and calculating – Electrical digital calculating computer – Particular function performed
Reexamination Certificate
1995-08-31
2002-05-07
Moise, Emmanuel L. (Department: 2133)
Electrical computers: arithmetic processing and calculating
Electrical digital calculating computer
Particular function performed
C708S523000, C708S524000, C708S603000, C708S626000, C712S221000
Reexamination Certificate
active
06385634
ABSTRACT:
BACKGROUND OF THE INVENTION
1. Field of Invention
In particular, the invention relates to the field of computer systems. More specifically, the invention relates to the area of packed data operations.
2. Description of Related Art
In typical computer systems, processors are implemented to operate on values represented by a large number of bits (e.g., 64) using instructions that produce one result. For example, the execution of an add instruction will add together a first 64-bit value and a second 64-bit value and store the result as a third 64-bit value. However, multimedia applications (e.g., applications targeted at computer supported cooperation (CSC—the integration of teleconferencing with mixed media data manipulation), 2D/3D graphics, image processing, video compression/decompression, recognition algorithms and audio manipulation) require the manipulation of large amounts of data which may be represented in a small number of bits. For example, graphical data typically requires 8 or 16 bits and sound data typically requires 8 or 16 bits. Each of these multimedia application requires one or more algorithms, each requiring a number of operations. For example, an algorithm may require an add, compare and shift operation.
To improve efficiency of multimedia applications (as well as other applications that have the same characteristics), prior art processors provide packed data formats. A packed data format is one in which the bits typically used to represent a single value are broken into a number of fixed sized data elements, each of which represents a separate value. For example, a 64-bit register may be broken into two 32-bit elements, each of which represents a separate 32-bit value. In addition, these prior art processors provide instructions for separately manipulating each element in these packed data types in parallel. For example, a packed add instruction adds together corresponding data elements from a first packed data and a second packed data. Thus, if a multimedia algorithm requires a loop containing five operations that must be performed on a large number of data elements, it is desirable to pack the data and perform these operations in parallel using packed data instructions. In this manner, these processors can more efficiently process multimedia applications.
However, if the loop of operations contains an operation that cannot be performed by the processor on packed data (i.e., the processor lacks the appropriate instruction), the data will have to be unpacked to perform the operation. For example, if the multimedia algorithm requires an add operation and the previously described packed add instruction is not available, the programmer must unpack both the first packed data and the second packed data (i.e., separate the elements comprising both the first packed data and the second packed data), add the separated elements together individually, and then pack the results into a packed result for further packed processing. The processing time required to perform such packing and unpacking often negates the performance advantage for which packed data formats are provided. Therefore, it is desirable to incorporate in a computer system a set of packed data instructions that provide all the required operations for typical multimedia algorithms. However, due to the limited die area on today's general purpose microprocessors, the number of instructions which may be added is limited. Therefore, it is desirable to invent instructions that provide both versatility (i.e. instructions which may be used in a wide variety of multimedia algorithms) and the greatest performance advantage.
One prior art technique for providing operations for use in multimedia algorithms is to couple a separate digital signaling processor (DSP) to an existing general purpose processor (e.g., The Intel® 486 manufactured by Intel Corporation of Santa Clara, Calif.). The general purpose processor allocates jobs that can be performed using packed data (e.g., video processing) to the DSP.
One such prior art DSP includes a multiply accumulate instruction that adds to an accumulation value the results of multiplying together two values. (see Kawakami, Yuichi, et al., “A Single-Chip Digital Signal Processor for Voiceband Applications”, IEEE International Solid-State Circuits Conference, 1980, pp. 40-41). An example of the multiply accumulate operation for this DSP is shown below in Table 1, where the instruction is performed on the data values A
1
and B
1
accessed as Source
1
and Source
2
, respectively.
TABLE 1
Multiply-Accumulate Source1, Source2
A
1
Source1
B
1
Source2
=
A
1
B
1
+ Accumulation Value
Result1
One limitation of this prior art instruction is its limited efficiency—i.e., it only operates on 2 values and an accumulation value. For example, to multiply and accumulate two sets of 2 values requires the following 2 instructions performed serially: 1) multiply accumulate the first value from the first set, the first value from the second set, and an accumulation value of zero to generate an intermediate accumulation value; 2) multiply accumulate the second value from the first set, the second value from the second set, and the intermediate accumulation value to generate the result.
Another prior art DSP includes a multiply accumulate instruction that operates on two sets of two values and an accumulation value (See “Digital Signal Processor with Parallel Multipliers”, U.S. Pat. No. 4,771,379—referred to herein as the “Ando et al.” reference). An example of the multiply accumulate instruction for this DSP is shown below in Table 2, where the instruction is performed on the data values A
1
, A
2
, B
1
and B
2
accessed as Source
1
-
4
, respectively.
TABLE 2
Using this prior art technique, two sets of 2 values are multiplied and then added to an accumulation value in one instruction.
This multiply accumulate instruction has limited versatility because it always adds to the accumulation value. As a result, it is difficult to use the instruction for operations other than multiply accumulate. For example, the multiplication of complex numbers is commonly used in multimedia applications. The multiplication of two complex number (e.g., r
1
i
1
and r
2
i
2
) is performed according to the following equation:
Real Component=
r
1
·r
2
−i
1
·i
2
.
Imaginary Component=
r
1
·i
2
+r
2
·i
1
.
This prior art DSP cannot perform the function of multiplying together two complex numbers using one multiply accumulate instruction.
The limitations of this multiply accumulate instruction can be more clearly seen when the result of such a calculation is needed in a subsequent multiplication operation rather than an accumulation. For example, if the real component were calculated using this prior art DSP, the accumulation value would need to be initialized to zero in order to correctly compute the result. Then the accumulation value would again need to be initialized to zero in order to calculate the imaginary component. To perform another complex multiplication on the resulting complex number and a third complex number (e.g., r
3
, i
3
), the resulting complex number must be rescaled and stored into the acceptable memory format and the accumulation value must again be initialized to zero. Then, the complex multiplication can be performed as described above. In each of these operations the ALU, which is devoted to the accumulation value, is superfluous hardware and extra instructions are needed to re-initialize this accumulation value. These extra instructions would otherwise have been unnecessary.
A further limitation of this prior art technique is that the data must be accessed through expensive multi-ported memory. This is because the multipliers are connected directly with data memories. Therefore the amount of parallelism which can be exploited is limited to a small number by the cost of the interconnection, and the fact that this interconnection is not decoupled from the instruction.
The Ando, et al. reference also describes that an alternative to this expensive in
Dulong Carole
Eitan Benny
Kowashi Eiichi
Mennemeier Larry M.
Mittal Millind
Blakely , Sokoloff, Taylor & Zafman LLP
Intel Corporation
Moise Emmanuel L.
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