Abstract:
Computing the Q and the P syndromes, which is needed in RAID 6 systems is effected through use of a single ROM lookup table for the necessary finite field multiplication. In one embodiment, the P and Q syndromes for data that normally arrives with 8-bit words are created by using Galois Field GF(2 4 ) arithmetic rather than the conventional GF(2 8 ) arithmetic, thereby very significantly reducing the requires size of the lookup table.

Description:
BACKGROUND 
     This invention relates to processing circuits. 
     RAID (Redundant Array of Independent Drives) is a technique for creating what appears to be single logical storage device out of an array of physical hard drives, such as drives  11  in  FIG. 1 . The most common RAID technique is RAID level 5, in which a set of n separate physical hard drives are coalesced into a single memory array. The array is divided into stripes, as shown for example in  FIG. 1 , with a portion of each stripe—a “strip”—stored on each of the different physical drives in the set. Thus, n−1 of the strips hold data, and the n th  strip holds parity information. The simplest way to visualize this arrangement is to think of one of the n hard drives holding the parity information. Many implementations, however, change the hard drive that holds the parity data from stripe to stripe. 
     When it is known that one of the hard drives that holds data fails to output proper data, the missing data can be reconstituted from the parity data. That is, when respective disk controllers  12  are able to report to array controller  13  that an error condition exists, controller  13  can recover the missing data, which allows the calling process to continue working while maintenance can take place on the failed drive, unaware that a problem was discovered. When data of a known drive is know to be wrong (and typically missing) the error is said to be an erasure error. As is well known, however, a single parity allows only one error can be detected (under the assumption that the probability of any other odd number of errors occurring concurrently is essentially zero), and thus when the location of the error is known (as in the case of erasure errors) the detected error can be corrected. 
     RAID level 6, which has recently been gaining in usage, employs two (or more) strips per stripe to hold redundant data, as illustrated in  FIG. 2  for a system that employs exactly two strips per stripe to hold redundant data. The aim of such a RAID 6 system is to protect the array against two concurrent error conditions. 
     In both RAID 5 and RAID 6 systems the redundant data can be viewed as degenerates of a Reed-Solomon error-correcting code, based, for example, on Galois field GF(2 8 ). The first redundant data strip (applies to both RAID 5 and RAID 6) holds the syndrome
 
 P=D   0   +D   1   + . . . +D   n-1   (1)
 
and the second redundant data strip (RAID 6) holds the syndrome
 
 Q=g   0   ·D   0   +g   1   ·D   1   + . . . +g   n-1   ·D   n-1   (2)
 
where the polynomial g is a generator of the field and the “·” is multiplication over the field (which is NOT the normal multiplication), and the “+” designates the XOR operation. In GF(2 8 ) there are 256 polynomial (g i ) coefficients, running from 0 to 255 and, therefore, equation (2) can handle 256 D i  elements. If each D i  element corresponds to the data of a strip, then operating in GF(2 8 ) allows use of 256 data strips. Adding a strip for the P syndrome and a strip for the Q syndrome results in a maximum array of 258 hard drives, each of which stores/outputs 8 bit bytes.
 
     There is another type of error for which current RAID techniques do not compensate, and that is the undetected read error. This occurs when, for a variety of reasons, controllers  12  fail to report a read error, and thus without an alert controller  13  provides the wrong value for a read request. Such events are uncommonly rare—a bit error rate of 1 in 10 17  or less—and are thus usually ignored because a typical consumer desktop hard drive may go several years without a single such error. 
     However, the situation for a large RAID array experiencing continual usage is quite different. An array of 20 drives that runs in a 24×7 environment can read as many as 3×10 17  bits/year, and can thus experience multiple undetected read errors per year. Each is potentially a catastrophic event, because it may result in the altering of a mission-critical value; for example, a bank account balance, a missile launch code, etc. The silent nature of the error means that it cannot be trapped, and thus no corrective action can be taken by software or manual means. 
     Clearly, at least in some applications, it is desirable to have a means for detecting and correcting unreported errors, and in a co-pending application titled, Error Rate Reduction for Memory Arrays, and which is filed simultaneously with this application, a method is disclosed where at each “read” operation one of the syndromes is computed. It is desirable to have a quick and inexpensive way for computing these syndromes. 
     SUMMARY OF DISCLOSURE 
     In the course of storing data in a RAID 6 system both the P and the Q syndromes need to be computed in order to correct and detect an unreported error, and computing the Q syndrome involves multiple finite field multiplications and XOR operations. An advance in the art is achieved by reducing the complexity and/or necessary time for computing the P and Q syndromes by using tables stored in ROMs. In one embodiment, finite field multiplication is effected with single lookup of a table. In another embodiment, both the Q and P syndromes obtained directly from a table. In still another embodiment, the P and Q syndromes for data that normally arrives with 8-bit words are created by using Galois Field GF(2 4 ) arithmetic rather than the conventional GF(2 8 ) arithmetic, thereby very significantly reducing the requires size of the lookup table or tables. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWING 
         FIG. 1  depicts a disk array where data is stored in stripes of the array, where each stripe consists a strip in each of the disk, and where at least one of the strips provides a measure of redundancy for error control; 
         FIG. 2  depicts a RAID 6 disk array in accord with the principles disclosed herein; 
         FIG. 3  depicts one embodiment of a disk array implementation that employs GF(2 4 ) processing; 
         FIG. 4  depicts another embodiment of a disk array implementation that employs GF(2 4 ) processing ;and 
         FIG. 5  shows an implementation that employs one single ROM-based lookup table for efficiently computing the Q syndrome for a RAID 6 array. 
     
    
    
     DETAILED DESCRIPTION 
     As indicated above, in both RAID 5 and RAID 6 systems the redundant data can be viewed as degenerates of a Reed-Solomon error-correcting code that is based, for example, on Galois field GF(2 8 ). That is, the RAID 5 parity check corresponds to an RS(n,n−1) code, where n is the number of drives in the array, and the RAID 6 P and Q signatures are a RS(n,n−2) code. 
     Under the assumption that only one read error occurs that is not caught by controllers  12 , in accord with the principles disclosed herein, data from the syndrome parity strip P is employed by array controller  13  as part of all read requests, and parity P′ is computed in accordance with equation (1), and compared to the read parity P. When P′≠P it is concluded that an undetected read error has occurred, in which case data from syndrome strip Q is also used. The actual location of the error bit is determined, and the correct value is computed and substituted for erroneous data. This allows the error to be silently corrected without impacting the calling process. 
     To implement the above-disclosed approach, controller  13 , which is the element that controls the entire array of hard drives, is modified to perform the error detection and correction. Specifically, when controller  12  is implemented with a stored program controlled processor and specialized hardware as disclosed below, the processor includes a subroutine such as the following read-data(address) subroutine: 
     
       
         
               
             
           
               
                   
               
             
             
               
                  read_data(address) /read data from the array at ‘address’ 
               
               
                 { 
               
               
                  read_disk_arrary(D) /obtain the data from the individual disks (strips) 
               
               
                  p=identify_P_strip(address) /identify the strip that holds P 
               
               
                  P′=compute_P_excluding_strip(p) /compute P′ 
               
               
                  if D(a)&lt; &gt;P′ then /error condition if read P is not the same as P′ 
               
               
                   q=identify_Q_strip(address) /identify the strip that holds Q 
               
               
                   fixError( ) /fix error 
               
               
                  End if 
               
               
                 } 
               
               
                   
               
             
          
         
       
     
     Of course, in order to fix the error, one must identify the strip in which the error occurs. Numerous techniques are known in the art for finding the strip that contains the error, e.g., Euclid&#39;s algorithm, Berlekamp-Massey, or some other similar well-known technique). See, for example, U.S. Pat. No. 5,170,399. The illustrative approach described below is a step-wise approach that is easy to understand. The algorithm considers each of the strips and computes a replacement D′ for the considered strip based on the other strips and on the parity strip a replacement value. If the computed D′ value is different from the read value then it is known that the strip under consideration is not the strip that contains the error. 
     fixError( ) 
     { 
     For i=0 to (n−1)
         compute D(j=i) from the other D(j&lt; &gt;i) values and P   compute Q′ using the computed D(j=i).   if Q′&lt; &gt;Q then continue   else exit   end if       

     next 
     } 
     In a RAID 5 implementation, the only redundant data is the P′ data, and therefore the presence of an unreported error can be deduced, but the location of the error itself cannot be ascertained. The error can be thus reported, but not corrected. Therefore, controller  13  propagates the error back up to the calling process to handle as it sees fit. 
     In the course of storing data in the  FIG. 2  array, and in the course of performing the fixError( ) function, the Q syndrome needs to be determined. Since multiplication over the GF(2 8 ) field that is necessary to effect (see equation (2) above) is quite complex, it is useful to take advantage of one or more lookup tables. 
     One approach that is highly efficient is to use a lookup table for the P and the Q syndromes, implemented in one or two ROMs. The input to the address port of the ROM is the concatenation of the data for which the syndromes need to be computed. To illustrate in connection with  FIG. 2 , where three data-holding strips are explicitly shown—each of which being one an 8-bit byte—in addition to the two redundant-data-holding strips, assuming that there are only the 3 data-holding strips, the address input to ROM  14  (which outputs an 8 bit byte corresponding to the P syndrome of equation (1)) is 24 bits long, which corresponds to an ROM that has a 24 bit address bus and stores 2 24  8 bit bytes i.e., 16 GBytes. The same is true for ROM  15 , which outputs an 8 bit byte corresponding to the Q syndrome of equation (2). 
     In connection with the correcting of errors not reported by controllers  12 , the above disclosed functions are carried out in processor  16  which, conveniently, may be a stored program controlled microprocessor. 
     To summarize a RAID 6 memory system that can store and deliver words that are 32 bits long can be implemented effectively with two ROMs, each of which has 16 Gbytes. 
     It may be observed that the above-disclosed approach of employing a ROM for developing the Q syndrome quickly becomes impractical to implement with current day ROM storage technologies. Four strips that hold 8-bit data (64-bit words) require a ROM for the Q syndrome that is 4 TBytes; and that is probably too large a memory for what can be economically purchased today. 
     An additional advance in the art is realized by employing GF(2 4 ) rather than GF(2 8 ). Working with GF(2 4 ), the maximum number of data-holding strips that can be handled drops from 256 to 16, and each of the strips is a 4-bit nibble, which offers users a maximum word size of 64 bits. 
     One approach for implementing a RAID 6 array that is based on GF(2 4 ) is to use hard drives the store/output 4 bit-nibbles. If one is constrained to use hard drives that inherently operate with 8-bit bytes, this can be achieved simply by having a selector at the output of the hard drive that, based on one of the address bits (e.g., the least significant bit) exposes one or the other 4 bit nibble in the 8-bit word. An implementation along these lines is depicted in  FIG. 3 , which uses 3 data-holding hard drives. On the positive side, it should be noted that each of the ROM&#39;s holds only 2 12  entries (4 Kbytes), as compared to the 2 24  entries in the GF(2 8 ) implementation, and the entries are only 4 bits long as compared to 8 bit entries in the GF(2 8 ) implementation—which allows using one ROM that outputs 8 bits per address (4 bits for the P syndrome and 4 bits for the Q syndrome). On the negative side, each clock cycle handles only words that are 12 bits long compared to the 24 bits in the above-disclosed GF(2 8 ) implementation. 
       FIG. 4  depicts an implementation that handles 24 bits, and it should be noted that it requires a total of 4 ROM&#39;s each of which has 2 12  entries that are 4 bits long, or 2 ROMs each of which has 2 12  entries that are 8 bits long. Compared to the GF(2 8 ) implementation that requires 2 ROMs that each contains 2 24  entries, the  FIG. 4  embodiment which requires 2 ROMs that each contains 2 12  entries is very significantly less demanding. It may be noted that the  FIG. 4  embodiment is limited to using not more than 16 hard drives, each providing 8 bits. 
     Another approach for computing the values of the Q and P syndromes that is not so limited focuses on the actual calculations that are represented by equations (1) and (2). Equation (1) is quite simple, since all that it requires is an XOR operation on n terms. Equation (2), however, requires n multiplications and XOR operations, and the bottleneck is the finite field multiplication across the GF(2 8 ) Galois field. 
     Typically such multiplication is accelerated by taking the logarithm of both operands, adding the results module  2   8  and then taking the anti-logarithm. This approach requires a log lookup table and an anti-log lookup table, and the operation requires 2 lookups of the log table, one modulo addition, and one lookup of the anti-log table, for a total of 3n lookups, n modulo additions, and (n−1) XOR operations; a total of 5n−1 operations. 
     An advance in the art is realized by coalescing the three lookups and the modulo addition into a single table (a ROM), resulting in only n lookups and n−1 XOR operations, for a total of 2n−1 operations. The inputs to the ROM are a generator coefficient and a corresponding data word, for example, g 1  and D 1 , each of which is 8 bits long. Hence, the ROM needs to have only 2 16  8 bit entries. This is depicted in  FIG. 5 , which includes a small controller to select the generator coefficient that is extracted from a generator coefficients ROM and the data elements that is routed to the output of the selector. The selected elements are applied to the aforementioned ROM, and the output of the ROM is applied to an XOR circuit whose output is fed back to the XOR circuit.