Abstract:
A low cost and high speed equalizing receiver structure is provided for improved inter-chip and inter-module communications. The receiver is able to recover data from a corrupted waveform from a signal wire such as one found on data, address or control wires in a microsystem architecture. The receiver can be used with binary as well as m-ary pulse amplitude modulation schemes. The receiver can be used to increase the sustainable data rate between chips or can be used to sustain a given data rate over a poorer quality channel as compared to prior art interconnect technologies. Methods for training and operating the receiver structure are provided. Novel systems whose performance is improved by incorporating the receiver structure are taught.

Description:
BACKGROUND OF THE INVENTION 
     1. Field of the Invention 
     This invention relates generally to VLSI circuits. More particularly, the invention relates to low cost receiver structures and methods to provide high-speed inter-chip or inter-module communication links. 
     2. Description of the Related Art 
     Communication between chips on a circuit board traditionally use very simple binary zero-one logic. A high voltage is sent to represent a binary one, and a zero voltage is sent to represent a binary zero. The receiver maintains clock synchronization with the transmitter and at the appropriate time decides a binary one if the voltage on the communication wire is above a threshold and decides a binary zero if the voltage is below another threshold. More recently it has been proposed to use multilevel signaling such as pulse-amplitude modulation in order to increase the data rate between chips. U.S. Pat. No. 6,005,895 discusses such a scheme. Another multilevel signaling approach for inter-chip interconnects is described in J. Zerbe et al., “1.6 Gb/s/pin 4-PAM signaling and circuits for multi-drop bus,” 2000 Symposium on VLSI Circuits, pp. 128-131, IEEE Press. This reference is referred to as the “Zerbe reference” henceforth. 
     While these multilevel signaling approaches are advantageous, inter-chip communication speeds are eventually limited by a phenomenon known in the art as “inter-symbol interference” or, “eye-closing.” Eye closing occurs when distortions introduced by the communication channel make it impossible to discern the transmitted signal levels by sampling the received waveform. The so-called “eye” refers to a pattern observed on an oscilloscope. When the eye is open, distinct signal levels can be viewed. When the eye is closed, the signal levels have run together and therefore distinct signal values cannot be observed. The problem of eye closing becomes more severe on a given connection as the data rate is increased. While for a fixed data rate it may be possible to assure the eye will stay open for short and well engineered point-to-point connections, this is not the case for multi-drop busses and/or longer runs as may be needed to support various system topologies. In future wafer scale designs, the same problems may occur for longer runs between intra-wafer modules. 
     In the field of wireline and wireless communications, various approaches to recovering data streams from received waveforms having closed eyes are known. Typically equalizers are used to open the closed eye so that the data may be properly recovered. Equalization approaches are multiply-accumulate intensive and rely on DSP (digital signal processing). Hence prior art solutions are too expensive for inter-chip applications where the symbol rates are presently in the 800 MHz region. To cross beyond the 800 MHz barrier, improved equalizing receiver structures are needed, but these would need to be able to operate at symbol rates in excess of 800 MHz. Such high-speed equalizers might also need to be able to differentiate more than two signal levels in a multilevel PAM (pulse-amplitude modulation) scheme. Prior art DSP-based equalizers are not suited to solve such inter-chip equalization problems in a cost efficient way. 
     It would be desirable to have a receiver structure for inter-chip communications that could perform equalization to open a closed eye pattern in a received signal. It would be desirable if such a receiver could be low cost in terms of silicon area and power consumption. It would be desirable for the receiver to not require, multiplications as are usually needed in equalizers, because multiplcations are very expensive. It would be desirable to have a receiver structure that could loosen design constraints on the physical channel between the chips by allowing reliable communications over channels involving longer runs and multiple drops. This would allow a given data transfer rate to be supported over a wider variety of wire-routing topologies, thereby increasing design flexibility. It would also be desirable to have a receiver that could increase the sustainable data transfer rate on a well-engineered circuit path. Accompanying system level application architectures that make use of the high speed interconnect are also taught. Methods of training and operating the receivers and systems of the present invention are also developed. 
     SUMMARY OF THE INVENTION 
     The present invention overcomes difficulties with prior art inter-chip and inter-module interconnects by introducing a low cost and low power equalizing receiver structure for inter-chip communications. The novel receiver structure allows binary and multilevel signaling to be received at greater speeds and over more diverse paths by processing the received signal prior to signal symbol detection. The equalizer structure can inherently operate at high speeds due to its multiply-free architecture. Both serial and parallel circuit structures are taught. Either of these structures or a hybrid of the two can be selected in light of design constraints. Systems based on symbol-spaced and fractionally-spaced sampling are taught. The equalizer is adaptive, but only needs to be adapted at power-up and can be optionally retuned periodically. 
    
    
     BRIEF DESCRIPTION OF THE FIGURES 
     The various novel features of the present invention are illustrated in the figures listed below and described in the detailed description which follows. 
     FIG. 1 is a block diagram illustrating a computer based system employing an inter-module interconnect that uses an equalizing receiver in accordance with the present invention. 
     FIG. 2 is a block diagram illustrating the mathematics of adaptive equalization and provides a system level view of aspects of the present invention. 
     FIG. 3 is a block diagram illustrating a multiplier-free receiver structure for equalizing and recovering a corrupted data signal. 
     FIG. 4 is a block diagram illustrating an embodiment of a shift array. 
     FIG. 5 is block diagram illustrating an embodiment of a tree adder/subtractor array. 
     FIG. 6 is a block diagram illustrating a serial logic based structure for multiplier-free data filtering. 
     FIG. 7 is a flow chart illustrating a method of training and operating the present invention for use in high-speed applications processing. 
    
    
     DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS 
     FIG. 1 is a block diagram illustrating an exemplary electronic system  100  making use of a bus line receiver structure in accordance with the present invention. A processing device  105  is illustrated that may be implemented with various combinations of one or more bus receiver modules ( 110 ,  135  and logic coupling to bus  155 ). These modules may be implemented on one or more single chip dies. In a preferred embodiment the processing device  105  is implemented as a microsystem on a single die. In most preferred embodiments, the bus receiver modules also include transmit (write) capabilities and are technically “transceivers modules.” As this application focuses mainly on the bus receiver aspect, these modules will be discussed as receivers, but at times may also be referred to as “transceivers.” It is to be understood that the bus interconnects usually include both read and write capabilities. In this application it is assumed that the bus receiver is responsible, at least in part, for equalizing a corrupted received waveform. 
     A first receiver module  110  is coupled via a point-to-point high speed interconnect  115  to an external device  120  such as a memory subsystem module. The interconnect  115  involves one or more wires and is engineered for high-speed inter-chip data transmission. An example of such a point-to-point connection is a Rambus Inc. DRAM interconnect; for example see FIG. 3 and FIG. 9 of U.S. Pat. No. 5,638,334. The interconnect has N 1  wires, where N 1  is a selected nonnegative integer. This interconnect may use binary or multilevel signaling (e.g., multilevel PAM). Each such high speed interconnect wire for communicating among circuit modules is referred to herein as a “high-speed bus wire,” and high speed signals carried thereon are referred to as “high-speed bus wire data signals.” It is to be understood that such bus wires are for communicating with external circuit modules such as other chips on a circuit board or other subsystems on a wafer scale integrated system. Reliable communication with an external module at very high speeds (e.g., 800 MHz) requires processing to make correct symbol decisions. No such processing is required for internal communication within a circuit module. 
     The first receiver  110  is also coupled to an application logic module  130 . The application logic module  130  typically involves a processor, gate array, custom or semi-custom logic circuits, depending on the end application of the system  100 . A wide bus interconnect  125  is preferably used to transport data words assembled by the first receiver  110 . The application logic module  110  is also coupled to a second receiver  135 , preferably by a wide-bus interconnect  140 . The second receiver  135  is coupled to a second high speed bus  145  similar to the point-to-point bus  115 , but designed for multi-drop configurations. See the Zerbe reference for a discussion of examples of high speed multidrop busses that use binary and multilevel signaling. The second high speed bus  145  can connect to a plurality of external devices  150 . The external devices  150  typically involve memories, other processors, or I/O devices. 
     The logic module  130  is also coupled via a standard bus interface to an external bus  155 . The external bus  155  is similar in design to those found on microprocessors, microcontrollers, and DSPs for connecting to one or more external devices  160 . The external devices  160  typically involve memories, other processors, or I/O devices. It should be noted that the present invention involves a system having at least one of the bus  115  or the bus  145  and the corresponding receiver  110  or  135 . In a minimal embodiment only one of the bus  115 ,  145  is implemented and the implemented bus need only comprise a single inter-module wire for high-speed communication. This single wire can carry data and/or control signal information. Systems according to the present invention may include more than this minimal configuration, and the specific three-bus configuration of FIG. 1 is presented by way of example only. 
     The system  100  represents a computerized system architecture. Examples of computerized systems that can be implemented using this architecture include computer systems such as laptops, workstations and servers. The system  100  may also be used to implement embedded systems such as cell phones, hand held computing devices, Internet appliances, network routers, packet switches, communications switches, network processors, digital signal processing systems, high speed control, video and display systems, embedded processing systems, and other types of systems involving computerized processing. 
     In operation, the system  100  performs application processing. Data is received from at least one of the receiver  110  or the receiver  135  via a corresponding bus  115  or  145 . Received data is sampled at each bus I/O pad and digitized. The raw data digitized at the I/O pad may optionally be pre-equalized with an analog equalizer circuit to do the best possible job of obtaining an input signal. However, if the input signal is viewed on an oscilloscope, the pre-equalized signal may have a closed eye pattern. By having a closed eye, it is meant that the noise margin at the optimal sampling instants is not within a specified range needed to maintain a specified bit error rate requirement. 
     The present invention is operative to post-process a digitized signal. The digitized signal involves a stream of sampled and quantized digital values derived from an analog waveform. The digitization can occur directly after the I/O pad or after any analog preprocessing circuitry that may be present (e.g., amplifier and/or preequalizer). The present invention is also operative to adaptively train the equalization subsystem to operate in an optimal fashion. The present invention is also operative to provide high-speed applications systems and processing methods using increased inter-module data rates. The structures and methods used to carry out the modes of operation of FIG. 1 are discussed in connection with FIGS. 2-7. 
     FIG. 2 is a block diagram illustrating the mathematics that govern aspects of the present invention. While this mathematical structure is common to many forms of equalizers, it is used to explain the theory and operation of the present invention as well as various novel features specific to the present invention. This figure also provides a system level view of aspects of the present invention. 
     An input bus wire data signal r(t) is received from an inter-module I/O bus wire. For example, this bus wire can be any of the I/O lines of the buses  115  or  145 . Similarly it can be any inter-module wire used for high-speed communication in a microsystem. Most commonly, the bus wire is a wire of an inter-chip interconnect (e.g.,  115 ,  145 ) but can be any wire running between chips or between modules in a wafer scale design, as long as it is used to carry high speed data. By “high speed data” it is meant that the data rate is so high that the eye pattern as viewed at the receiving pin or behind an analog pre-equalizer circuit may be sufficiently closed to violate a noise margin constraint imposed by a set of system design requirements. It should be noted that the signal r(t) represents an analog signal received at the input signal point (e.g., after the I/O pad or after an analog signal conditioning circuit). 
     The signal r(t) is routed into an ADC (analog to digital converter)  205 . The ADC  205  may be designed in many ways. One example is the four-level ADC shown in FIG. 4 of the Zerbe reference. Similar but simplified structures can be designed to receive a two-level signal. Integrating and non-integrating two-level receivers are well known in the interconnect art. Any of these simple one or two bit converters may be used as the ADC  205 . 
     One aspect of the present involves some specific ADC configurations that impact downstream processing in the receiver. It is known from the art of delta sigma analog-to-digital converters that input signals can be over-sampled, quantized to just two levels, and the quantized values can be reconstructed to produce a multi-bit output after some post processing involving a low pass filter. Hence in one configuration, the ADC involves a delta sigma converter that over-samples the input data stream to either two or four bits. In such cases the ADC involves a quantizer and a feedback circuit as are known in the delta sigma converter art. Both two-level and four level delta sigma converter architectures are known, and any such delta sigma ADC structure may be used for the ADC  205 . 
     For use with the present invention, the over-sampling rate is normally chosen to be an integer in the range from one to sixteen, although higher rates are theoretically possible and are within the scope of the present invention. Because the symbol rate of the signal itself is on the order of 800 MHz or more, it is difficult to increase the oversampling rate much more that two to four times the symbol rate. However, it is anticipated that future systems may involve clock speeds that are higher and future systems may be limited by inter-module communications instead of on-chip clock rates. In such systems, the ADC  205  may be implemented to produce a two-level or four level output signal that is over-sampled by an appropriately chosen oversampling factor, OSF. The parameter OSF is chosen based on data rates and channel characteristics found in a given system and may be engineered using standard design practices. 
     To summarize, the output of the ADC may involve two-level or four-level digitized data. This digitized data may be directly quantized (e.g., an integrating A/D as in FIG. 4 of the Zerbe reference or a two-level variation). Alternatively, the digitized data may involve a delta sigma converter quantizer-output data stream (two-level or four-level coder output—e.g., the output of the block labeled “clock” in FIG. 9.15 of J. G. Proakis, et al., Digital Signal Processing, Principles, Algorithms and Applications, 3 rd  Ed., Prentice-Hall, 1996, the “Proakis reference” henceforth.). The delta-sigma quantized data stream is conventionally sent to a low-pass filter (delta sigma decoder) in order to recover a multilevel data value. Note that there are many encoder architectures for delta sigma ADC&#39;s and any of these may be used with the present invention. In the present invention, however, the quantized delta sigma data stream is fed into an equalizer structure in its over-sampled and quantized form. The present invention is preferably practiced where the ADC  205  generates and output stream quantized to either one or two bits (two levels or four levels). In some systems, recovered symbol values may be resolved to more levels than are provided by the quantizer in the ADC  205 . 
     The output of the ADC  205  is coupled to a feed-forward filter  210 . The feed-forward filter uses an FIR filter structure as is well known in the art. As will be discussed, because the ADC  205  generates one or two bit values, the feed-forward filter may be implemented with multiplier-free circuits. The output of the feed-forward filter is coupled to an optional summing circuit  215 . The output of the summing circuit  215  is coupled to an optional delay locked loop  220 . The delay locked look may be implemented with a phase locked loop, and the construction of such delay locked loops is well known to skilled artisans. See for example, Sidoropoulos et al., 2000 Symposium on VLSI Circuits, pp. 124,127, IEEE Press. The output of the delay locked loop  220  is coupled to the ADC  220  to control the sampling times. In some embodiments, especially those involving significant oversampling, the DLL may be omitted. 
     The output of the summing circuit  215  is also coupled to a decision device  225 . The decision device quantizes the output of the summing circuit to a nearest symbol value at an appropriate symbol-sampling instant. The output of the decision device provides the recovered data output of the receiver structure. In systems where the sampling rate of the ADC  205  is OSF times the symbol rate, the symbol-sampling instant occurs once every OSF number of input samples. In some embodiments the decision device  225  may be replaced with a sequence detector such as one based on the Viterbi algorithm. However, due to the computational complexity of such devices, a direct signal slicer (e.g., quantize to nearest signal level) embodiment is considered to be preferred at this time. The output of the decision device  225  feeds to an optional feedback filter  230 . The feedback filter  230  is used to implement a decision feedback equalizer structure. The output of the decision-feedback filter, when present, is coupled into a second input to the summer  215 . 
     The feed-forward filter  210  and feedback filter  230  involve sets of coefficients, W FF  and W FB . These coefficients are determined by an adaptation algorithm module  240 . The operation of the adaptation module  240  is discussed in detail in connection with FIG.  7 . One embodiment whereby an error signal is developed in a differencing circuit  235  is illustrated. The adaptation algorithm can use various combinations of input values supplied by the ADC  205 , past decisions, and training (known reference) signal values (T in FIG. 2) in order to compute W FF  and W FB  to minimize a measure of the error signal output from the differencing circuit  235  or a measure of the difference between the output of the summing circuit  215  and the set of known reference values. Example algorithms that can be applied include a direct solution of a matrix least squares problem (preferred for most embodiments of the present invention), or sequential algorithms to include least mean squares adaptation, recursive least squares adaptation, or error-back propagation. For a background discussion of adaptive algorithms, see “Adaptive Filtering” by Simon Haykin, Prentice-Hall. 
     The operation of the system  200  will now be discussed in broad terms. The input signal r(t) is received from an inter-module bit line such as an inter-chip bus wire. The ADC  205  samples this signal periodically either at the symbol rate or with an over-sampling factor, OSF. The data is quantized to either one or two bits, depending on the embodiment, and may include delta sigma encoding. The digitized information is fed to the feed-forward filter  210 . The feed-forward filter output is processed using a multiplication free circuit structure adapted for equalization of very high data-rate signals. The output of the feed-forward filter is combined with the output of the optional decision feedback filter  230  to form a signal estimate. This signal estimate is then sliced to the nearest symbol value (by direct slicing or sequence estimation). The coefficients of the feed-forward and feedback filters are determined at power-up time using the adaptation algorithm  240 . The estimation signal y k  is optionally fed back to the DLL  220  to determine optimal sampling instances to control the ADC. In some embodiments a second DLL (not shown) can also be used to indicate the sampling instances for the decision device  225 . This DLL selects its sampling times to minimize the power in the signal output from the differencing circuit  235 . 
     FIG. 3 is a block diagram illustrating a specific equalizing receiver structure in accordance with the present invention. A signal arriving from an inter-module bus wire is digitized by the ADC converter  205 . The ADC  205  is discussed in detail in connection with FIG.  2 . The n-bit output (n=1 or n=2) is sent to a feed-forward buffer  305 . The feed-forward buffer  305  is typically implemented as either a physical tapped delay line shift register or a circularly addressed buffer. The feed-forward buffer  305  holds N FF  samples of input data, where N FF  is a nonnegative integer representing the FIR-filter order of the feed-forward filter  210 . In preferred embodiments, the buffer  305  includes a parallel set of outputs so the entire contents can be read in a single cycle. In some embodiments where n=2, an output multiplexer is used in each sample position and the contents can thereby be read out in two cycles. In still other embodiments the contents are read out in N FF  cycles, but this is not viewed as a preferred embodiment at this time based upon current circuit speeds. 
     The equalizing receiver structure  300  also includes an optional decision feedback data buffer  310 . This data buffer stores previously recovered symbol-decisions. For example, with 2-level PAM, the symbol decisions comprise previously decided 1-bit data values. With 4-level PAM, the symbol decisions comprise previously decided 2-bit data values. The outputs of the feed-forward buffer  305  and the feedback buffer  310  are coupled through a routing network  315  to control an optional shift array  330  and an adder tree  340 . The optional shift array receives control inputs from the routing network  315  and data values from a coefficient RAM  335 . The coefficient RAM stores the filter coefficient vector W FF  and, when decision feedback is implemented, W FB . The data output of the shift array  320  is coupled to an adder array  340 . When the shift array  320  is not implemented, the output of the coefficient RAM  335  couples directly into the adder array  340 . The output of the adder array couples to the decision circuit  225  and to the optional DLL  220 . 
     In some systems, some of the coefficients stored in the coefficient RAM  335  rout to the shift array  330  while other coefficients route directly to the adder array  320 . This occurs, for example when the feedforward buffer  305  holds 1-bit data and the feedback buffer  310  stores 2-bit symbol decision values (e.g., 4-level PAM symbol decisions). In such cases, the shift array may be viewed as having hard-wired empty shift cells (straight-through routing) that selectively always decides not to shift certain coefficients. For coefficients that may be shifted in this example, these coefficient values route through a shifter that selectively shifts or does not shift based on a value in the feedback buffer. 
     The routing network  315  may be implemented in a number of ways. In one type of embodiment, the feed-forward buffer and the feedback buffers are implemented with serial shift register paths (one or more bits wide). In this case the routing network  315  comprises fixed connections that route buffer output values to appropriate control inputs to the shift array  320  and/or the adder array  340  as is discussed in connection with FIG.  4  and FIG.  5 . In embodiments where circular addressing is used, the routing network may be used to route the control inputs to the shift array  330  and/or the adder array  340  over switched connections. In still another type embodiment, the router network  315  may involve fixed control connections and the coefficient RAM outputs may be sequenced to route to the appropriate data input to the shift array  330  or the adder array  340 . This type of embodiment is not preferred in many cases because it the coefficient data width is usually wider than the widths of the words stored in the feed-forward and feedback buffers. 
     The operation of the equalizing receiver  300  will be discussed subsequently in light of the discussions of FIGS. 4-7. 
     FIG. 4 illustrates an embodiment of the shift array  330 . In this embodiment, the buffers  305  and  310  are implemented as serial shift registers, two bits wide, with parallel outputs. The four bit values can be considered to take on the values {−2, −1, 1, 2}. While other encodings would be obvious to those skilled in the art, for simplicity of discussion, each two bit value in the buffers  305 ,  310  is considered to be in sign-magnitude form with one sign bit and one magnitude bit. 
     The coefficient RAM  335  is shown as a parallel output device whose output values couple each to a shift device  400 . The coefficient RAM stores the elements of the feed-forward and feedback coefficient vectors, W FF  and W FB . The shift array is optional because embodiments can be developed where the ADC  205  quantizes data values to only one bit. In this case the one-bit digital values are considered to take on the two values {−1, 1}. 
     In systems where the input ADC  205  quantizes the input waveform to two bits, the magnitude bit is applied to a control input of each shifter  400 . If the magnitude bit has a one value, the shifter performs a left arithmetic shift of one bit. If the magnitude bit has a zero value, the shifter does not perform any shift. 
     In some systems a two&#39;s complement shifter can be used. In such embodiments the sign bit is also applied to the shifter. If the sign bit is a one, then the shifter additionally computes the two&#39;s complement negation of the input. If the sign bit is a zero, no two&#39;s complement arithmetic negation is computed. In systems where only one bit is used, the shifter  400  does not shift but only performs the two&#39;s complement negation function. As will be discussed, the two&#39;s complement negation function can optionally be implemented in the adder array. 
     It should be noted that the coefficient RAM  335  may be viewed as a smart memory with computationally modifiable outputs. Associated with each shifter  400  is a coefficient memory location. The shifter  400  may be viewed as an output circuit for the corresponding coefficient memory word. The smart memory outputs a coefficient that may optionally be shifted and negated in accordance with the associated control inputs that are stored in the buffers  305  and/or  310 . Instead of running address lines to the memory, the control inputs tell how to preprocess the memory contents for subsequent accumulation. As is discussed in connection with FIG. 6, in some systems the output preprocessing circuits may be shared by multiple memory locations. In such systems address lines are used to sequence the coefficients out from a collection of locations through an output preprocessing circuit. The preprocessed outputs are then accumulated using a circuit as discussed in connection with FIG.  6 . 
     Referring now to FIG. 5, an embodiment of a portion of the adder array  340  is illustrated in block diagram form. The data inputs to the adder array correspond to the outputs of the shifters  400 . If the shifters  400  are not implemented, then the data inputs come directly from the outputs of the coefficient RAM  335 . The illustrative embodiment of the adder array uses a binary tree architecture, although other architectures may be implemented as discussed in connection with FIG.  6 . 
     In the illustrative embodiment, the adder array is designed to combine four inputs, S 1 , S 2 , S 3  and S 4 . As is well known, larger binary tree adder structures can be similarly constructed to combine more than four inputs. In general log 2 (N) cascaded stages of adders are needed to combine N inputs. Note that the adder of FIG. 5 combines four inputs and involves log 2 (4)=2 cascaded stages. 
     If the shifters  400  are implemented that perform two&#39;s complement negation, then all the array adder needs to do is add the four inputs together. If the shifters  400  are not used, or if the shifters  400  perform shifting but not two&#39;s complement negation, then the adder array  340  needs to compute a linear combination of S 1 , S 2 , S 3  and S 4  involving both additions and subtractions. The embodiment shown in FIG. 5 assumes that the shifters do not perform two&#39;s complement negation. As will be discussed, the illustrative embodiment of FIG. 5 can be readily simplified for the case where the shifters  400  do perform two&#39;s complement negation. 
     The first cascaded stage of the adder array  340  involves two adders  500  and  505 . The inputs of these adders are coupled to the outputs of the shifters  400  (when present, the coefficient RAM otherwise). The outputs of the adders  500  and  505  couple to the inputs of a third adder  510 . The third adder  510  is in the second cascaded stage of the adder array. Under the assumption that the shifters do not perform two&#39;s complement negation, each adder in the first stage receives two control bits. These control bits correspond to sign bits of entries in the data buffers  305  and  310 . Similarly to FIG. 4, these sign bits route down from a corresponding location in one of the data buffers  305 ,  310  to the adder receiving the corresponding coefficient as an input. If the two sign-bit control inputs are (0,0) the adder  500  computes c=a+b. If the control inputs are (0,1) the adder  500  computes c=a−b. If the control inputs are (1,0), the adder  500  computes c=−a+b. If the control inputs are (1,1), the adder  500  computes c=−a−b. The adder  505  works similarly. The adder  510  always computes c=a+b. Skilled artisans will see readily see that other combinations of the control inputs can be applied to adders in different stages to produce the same results. All such embodiments are within the scope of the present invention. The adder array of FIG. 5 is shown by way of example only. As mentioned previously, if two&#39; complement negation is applied in the shifters  400 , then all of the adders can be replaced with simpler adders that only computer c=a+b. 
     The adder tree may also be considered to be a part of a smart memory output circuit. The coefficients are read out of memory either all in parallel, serially, or subsets are read in parallel and processed sequentially. This is discussed in further detail in connection with FIG.  6 . The output circuits of the smart memory are operative to selectively shift and negate the each coefficient memory word as it is read out of the smart memory. The adder tree extends this smart-memory output circuitry to combine the outputs into a linear combination of the coefficients to develop, at time k, the output y k . 
     Referring now to FIG. 6, an optional sequential processing circuit  600  is illustrated for the accumulation function. The sequential processing circuit may be used instead of or in combination with the adder array  340 . In a purely sequential embodiment, coefficients are sequenced out of memory along with the corresponding value from the data buffer to perform convolution based filtering. Known FIR filtering addressing schemes for shifted arrays or circular buffers can be used to ensure the coefficients and the data buffer values in an appropriately synchronized fashion to achieve convolution-based FIR feed-forward and decision feedback filtering. 
     When the synchronized pair of coefficient value and data buffer value meet at the optional shifter  400 , the coefficient is shifted or not shifted according to the magnitude bit in the data buffer (if four level input sampling is used). The output of the shifter  400  is coupled to an adder/subtractor  605 . If the corresponding data-buffer value&#39;s sign bit is one, the adder/subtractor computes c=b−a, otherwise it computes c=a+b. The output of the adder/subtractor is coupled to an accumulator register  610 . This circuit can be clocked N times to combine N coefficients to form the required FIR feed-forward and feedback convolution sums to produce the output of the summing device  215 . 
     As discussed previously, the shifter  400  can also be designed to perform negation. In such a case, both the magnitude and sign bits are sent to the shifter  400  and a simple adder that computes c−a+b is used. When the input data is sampled to only one bit, the this type of shifter embodiment would only receive the sign bit and would thus only perform the selective negation operation but not selective shifting. 
     Note that in general the sequential accumulator circuit  600  can compute a sum of N 2  terms using a single adder/subtractor. The adder array  340  can thus be constructed using a combination of binary tree adder structures such as shown in FIG.  5  and sequential accumulator structures as shown in FIG.  6 . For example, the first level adders  500 ,  510  can be replaced by the circuit  600  to form a partial accumulation value instead of using the two adder circuits  500 ,  510 . These concepts can be applied to replace any N 2  adders with a single accumulator circuit. The accumulator outputs can then be sent to successive stages employing individual adders or sequential accumulation circuits to add together the partial results. Using this approach, an adder array can be designed to provide a given tradeoff between clock cycles and silicon area. The full binary tree adder requires the fewest clock cycles and the most silicon area. The sequential accumulator requires the most clock cycles but the least silicon area. Hybrid parallel/sequential circuits fall somewhere in between and can be designed to meet a given design constraint. A major constraint is the circuit will have very few clock cycles to computer each output because the symbol rate will be very high, e.g. 800 MHz using today&#39;s technology. In the future, however, inter-chip communications physics will remain the same while on-chip clock speeds will scale upwards. Hence future systems will have a greater ability to trade silicon area for clock cycles. 
     Referring now to FIG. 7, a method  700  of operating the equalizing receiver structure  300  is illustrated in flow chart form. In a first step  705 , initial boot procedures are executed to initialize the processing state of the processor  105 . System boot procedures normally performed use the standard bus  155  or on-chip memory to support initial program execution and system configuration. Initially the transceivers  110  or  135  can operate the data paths  115  and/or  140  at lower speeds in order to read and write data reliably. For example, if the memory subsystem module  120  is a DRAM array, during boot time the transceiver  110  may write a known reference sequence out to the DRAM array. In some cases external devices may store a reference sequence in nonvolatile memory to avoid the need to write out a reference sequence. 
     Once certain boot procedures are performed, and usually as a part of an overall system boot procedure, control next passes to a step  710 . In the step  710  the reference sequence is read over a high-speed wire or bus such as the bus  115 . This sequence is read at a target operating speed and is digitized by the ADC  205 . Control next passes to a step  715  where a locally available version of the reference pattern accessed from memory. Preferably the training pattern involves a symbol sequence comprising two level of four level data (two bits per symbol, interpreted as either {−1, 1} or {−2, −1, 1,2}). 
     Control next passes to a step  720  where an adaptation algorithm is applied. In a preferred embodiment, a matrix least squares problem is solved. The problem is set up as follows. Suppose there are N values in the training sequence, and that W FF  has N FF  elements and W FB  has N FB  elements. Then a matrix AεR N×(N   FF   +N   FB   )  is constructed whose k th  row contains the contents of the data buffer  305  at time k based on the sampled input. The k th  row also contains the contents of the data buffer  310  at time k. That is, the k th  row is formed by augmenting the contents of the buffer  305  with the contents of the buffer  310 . The contents of the data buffer  310  are derived from “previously decided” samples drawn directly from the set of known reference values (training sequence). It can be noted that the matrix A may be constructed in many ways depending on the exact ordering of elements in the k th  row, but in many embodiments a block Toeplitz or a block Hankel matrix will result. Next a vector bεR N  is constructed, also using known reference values of the training sequence. The k th  element of the vector b contains the correct decision the equalizing receiver is supposed to make at time k. 
     Control next passes to a step  725  where the filter coefficients are derived. Preferably a matrix least squares problem of the form Ax=b is solved for a least squares solution vector x. With the problem so constructed, the first N FF  elements of x correspond to W FF  and the next N FB  elements of x correspond to W FB . Many approaches are known to solve matrix least squares problems are known in the art and, any of these can be used. 
     While the aforementioned matrix least squares solution is deemed to be preferable, other methods may also be applied. For example LMS or RLS adaptive filtering algorithms may be applied. In general any adaptive filtering algorithm that computes filter coefficients to cause an input signal to be matched to a known data sequence may be used. Blind adaptive filters or neural network methods may also be applied but are not deemed to be the best approach for use with the present invention. It can be noted that when recursive adaptation algorithms are used, the steps  710 ,  715 ,  720  and  725  occur in a looped and interleaved fashion. Such solutions are well known in the art (see the LMS and RLS algorithms, for example). 
     Control next passes to an optional decision-step  730 . The decision step  730  decides whether the residual error of the least squares problem, e=b−Ax has a small enough average magnitude. Alternatively, the step  730  runs a second training sequence through the system and measures the residual error of the recovered waveform, y k , in FIG.  2  and FIG. 3 (output of  235 ). If the error is sufficiently small enough to meet a bit error rate criterion, then the set is accepted. Otherwise the steps  710 - 725  are repeated using a different data rate. Different speeds can be checked by starting at a target highest speed, working down until a speed is found that meets requirements. Alternatively the process can start with a lower speed and keep working up until a speed is reached where the system will not meet the bit error rate requirement. In either case, the set of coefficients that work at the highest possible speed are preferably selected and the system is preferably operated at top speed. For power consumption reasons, more than one set of coefficients may be maintained to operate the bus at different speeds because full speed may not be needed in all cases. At lower speeds, it may be possible to simply digitize the output of the ADC  205  as the symbol decision because the eye of the input waveform may not be closed. In such cases the receiver  300  may be optionally bypassed and put in a sleep mode. 
     Note that when multiple bus wires are used, the steps  710 - 730  may proceed in parallel. The same training information may be used for each wire, or different training signals may be used for different wires. The steps  720  and  725  are typically performed in a time-multiplexed order. Although more computationally expensive, the data buffer  305  can be expanded to include samples from one or more adjacent wires. In such a system the aforementioned matrix-based training algorithm will derive a set of weights for these taps to minimize cross talk. In such systems the buffer  305  is fed from multiple input sources using the same approach as is illustrated at the top of FIG.  4 . In this type of embodiment the feed-forward buffer receives inputs from multiple ADCs in order to combat cross talk. In such systems the training data is collected in parallel and different training signals are used on adjacent wires. The training is otherwise performed in the same manner as described above. In this embodiment matrix row still contains the contents of the buffers  305  and  310 , but the source of the information in the buffer  305  comes from more than one ADC. Similarly, one or more decisions from adjacent channels may be fed back to the decision buffer  310  so that the decision feedback portion of the equalizer can take into account latent cross talk effects due to previously detected symbols. Such embodiments are optional. If a matrix least squares training algorithm is used, the matrix A is developed as discussed above by concatenating the buffers  305  and  310  together. In this construction the buffers  305  and  310  include tapped-delay line sub-buffers involving inputs fed from multiple ADC&#39;s. Viewed another way, a row is formed by augmenting the row formed by concatenating the buffers  305  and  310  from a given I/O channel. To this row are concatenated at least portions of the buffers  305  and or  310  from at least one other channel. Again, the exact ordering of data elements in a row is a design choice. 
     Control next passes to a step  735  where the coefficients are loaded into coefficient memory for system use in the coefficient RAM  335 . When the optional step  730  is used, the step  735  may be performed as a part of the step  730 . 
     Control next passes to a step  740  where the system  100  is operated using the receiver structure  300  in at least one of the transceivers  110  or  135 . The receiver  300  performs equalization using the trained coefficient sets W FF  and/or W FB . The system operates in a multiplier-free manner to open a closed eye on a inter-module wire such as a high-speed inter-chip bus wire. This method allows systems to be constructed and operated that can dedicate some silicon area to attain increased inter-module data rates, thereby increasing overall system performance. 
     Although not shown, the error as measured at the output of the differencing circuit  235  may be periodically or continuously monitored during system operation. In one embodiment, the differencing circuit  235  is implemented in hardware and is used to accumulate and error level by passing the error magnitudes to a first order recursive (IIR) filter. If the error level exceeds a threshold, an interrupt is generated and training is performed again for one or more bus wires to bring the system back into alignment. This feature is also optional. One example of a way to maintain an error level in a multiplier-free way is to use a recursive filter of the form p m =(1−2 −7 ) Pk −1 +|e k |. In 8-bit arithmetic, this only requires a shift-add operation. Saturating arithmetic may also be used, and that involves an extra operation for saturation control. 
     Now that the system and its operation have been described, a specific preferred mode of operation will be discussed in light of FIGS. 1-7. In a preferred mode of operation the ADC  205  is selected to be an oversampling delta sigma encoder. The quantizer in the delta sigma encoder is selected to be either two or four bits. The oversampling rate is typically chosen to be an integer, OSF, between one and sixteen. Based on present technological constraints, suppose the OSF parameter is set to two or four. This causes the data-clocking rate into the buffer  305  to be two or four times the symbol rate. If the serial type shifter/negator/accumulator  600  is used, running accumulations using two or four cycles each may be produced during a data symbol interval. This reduces the amount of hardware needed to implement the adder array  340 . Still, no multipliers are required, just simple one-bit shift devices and add/subtract type circuits. 
     The delta sigma data stream output from the ADC  205  is noisy, but the feed-forward filter W FF  has been adapted during training to take this into account. The fact that a delta sigma converter has been used allows the system to recover information with greater reliability and fidelity than when it was originally sampled. In essence, the delta sigma decoder is itself a decision feedback equalizer instead of a simple low pass filter. While sigma delta converters are normally designed to recover a large number of bits, the present invention is only concerned with recovering a small number of bits reliably. The sigma delta converter at the input allows equalization to be performed at very high clock rates with very simple hardware. When the input symbol rate is on the order of 800 MHz or higher, and when a given chip may require eight to thirty-two or more receivers for a given high speed bus, an architecture that can operate at very high clock rates with a minimum silicon footprint becomes crucial. This is achieved by the present invention by sampling (possibly oversampling) an input signal with a very low resolution and passing the signal through a high-speed, low complexity equalization device. 
     Another aspect of the present invention involves a mode of operation for the multi-drop bus  145 . The receiver  135  may be required to receive signals that originate from more than one high-speed data source  150 . In such cases the channel characteristics between the receiver  135  and each of the high-speed data sources  150  will generally be different. In such cases different sets of coefficients are preferably developed for each channel. The method  700  is carried out as illustrated in FIG. 7, but an extra feedback path (multidrop) is provided from the step  735  to the step  710 . The same receiver structure  300  is used, but the coefficient RAM  335  selectively outputs an appropriate set of coefficient values depending on from which of the sources  150  data is being received. In terms of FIG. 4, this involves adding standard memory addressing and output multiplexing circuits to the coefficient RAM  335 . The construction of addressable memories is well known in the art. 
     Although the present invention has been described with reference to specific embodiments, other embodiments may occur to those skilled in the art without deviating from the intended scope. It should be noted that certain novel aspects of the present invention involve improved inter-module communication links for high-speed busses in computerized systems, but some of the more general concepts could be applied to other systems as well. For example, the receiver  300  could be used in other types of applications such as wireline telecommunication systems and inter-computer cabling. For such systems the design constraints would change. Therefore, it is to be understood that the invention herein encompasses all such embodiments that do not depart from the spirit and scope of the invention as defined in the appended claims.