Dense Gray Codes in Mixed Radices

The standard binary reflected Gray code describes a sequence of integers 0 to n-1, where n is a power of 2, such that the binary representation of each integer in the sequence differs from the binary representation of the preceding integer in exactly one bit. In September 2016, we presented two methods to compute binary dense Gray codes, which extend the possible values of n to the set of all positive integers while preserving both the Gray-code property such that only one bit changes between each pair of consecutive binary numbers, and the density property such that the sequence contains exactly the n integers 0 to n-1. The first of the two methods produces a dense Gray code that does not have the cyclic property, meaning that the last integer and the first integer of the sequence do not differ in exactly one bit. The second method, based on the first, produces a cyclic dense Gray code if n is even. This thesis summarizes our previous work and generalizes the methods for binary dense Gray codes to arbitrary radices that may either be a single fixed radix for all digits or mixed radices where each digit may be represented in a different radix. We show how to produce a non-cyclic mixed-radix dense Gray code for any set of radices and any positive integer n---that is, a permutation of the sequence \u3c0,1,...,n-1\u3e such that the digit representation of each number differs from the digit representation of the preceding number in only one digit, and the values of the digits that differ is exactly 1. To this end, we provide a simple formula to compute each digit of each number in the permutation in constant time. Though we do not provide such a formula to generate the digits of a cyclic mixed-radix dense Gray code, we do present, for n equal to the product of the radices, a recursive algorithm that computes the entire cyclic mixed-radix Gray code with the density, strict Gray-code, and modular cyclic properties: given a k-tuple of mixed radices r = (r_(k-1),r_(k-2),...,r_0), each of the n integers in the cyclic mixed-radix Gray code differs from its preceding integer-with the first integer differing from the last integer---in only one digit position i, and the values of those digits differ by exactly 1, except for the digits of the first and last numbers, which may also be the integers 0 and r_i-1. For values of n that are less than the product of the radices, we show a list of cases for which we prove it is impossible to generate a mixed-radix dense Gray code that has the modular Gray-code and cyclic properties for a set of mixed radices r and a positive integer n

Systematic Error-Correcting Codes for Rank Modulation

The rank-modulation scheme has been recently proposed for efficiently storing data in nonvolatile memories. Error-correcting codes are essential for rank modulation, however, existing results have been limited. In this work we explore a new approach, \emph{systematic error-correcting codes for rank modulation}. Systematic codes have the benefits of enabling efficient information retrieval and potentially supporting more efficient encoding and decoding procedures. We study systematic codes for rank modulation under Kendall's $\tau$-metric as well as under the $\ell_\infty$-metric. In Kendall's $\tau$-metric we present $[k+2,k,3]$-systematic codes for correcting one error, which have optimal rates, unless systematic perfect codes exist. We also study the design of multi-error-correcting codes, and provide two explicit constructions, one resulting in $[n+1,k+1,2t+2]$ systematic codes with redundancy at most $2t+1$. We use non-constructive arguments to show the existence of $[n,k,n-k]$-systematic codes for general parameters. Furthermore, we prove that for rank modulation, systematic codes achieve the same capacity as general error-correcting codes. Finally, in the $\ell_\infty$-metric we construct two $[n,k,d]$ systematic multi-error-correcting codes, the first for the case of $d=O(1)$, and the second for $d=\Theta(n)$. In the latter case, the codes have the same asymptotic rate as the best codes currently known in this metric

Reordering Rows for Better Compression: Beyond the Lexicographic Order

Sorting database tables before compressing them improves the compression rate. Can we do better than the lexicographical order? For minimizing the number of runs in a run-length encoding compression scheme, the best approaches to row-ordering are derived from traveling salesman heuristics, although there is a significant trade-off between running time and compression. A new heuristic, Multiple Lists, which is a variant on Nearest Neighbor that trades off compression for a major running-time speedup, is a good option for very large tables. However, for some compression schemes, it is more important to generate long runs rather than few runs. For this case, another novel heuristic, Vortex, is promising. We find that we can improve run-length encoding up to a factor of 3 whereas we can improve prefix coding by up to 80%: these gains are on top of the gains due to lexicographically sorting the table. We prove that the new row reordering is optimal (within 10%) at minimizing the runs of identical values within columns, in a few cases.Comment: to appear in ACM TOD

Gray codes and their applications

An n-bit Gray code is an ordered set of all 2n binary strings of length n. The special property of this listing is that Hamming distance between consecutive vectors is exactly 1. If the last and first codeword also have a Hamming distance 1 then the code is said to be cyclic. This dissertation addresses problems dealing with the design and applications of new and existing types of both binary and non-binary Gray codes. It is shown how properties of certain Gray codes can be used to solve problems arising in different domains. New types of Gray codes to solve specific types of problems are also designed. We construct Gray codes over higher integral radices and show their applications. Applications of new classes of Gray codes defined over residue classes of Gaussian integers are also shown. We also propose new classes of binary Gray codes and prove some important properties of these codes

Resource placement, data rearrangement, and Hamiltonian cycles in torus networks

Many parallel machines, both commercial and experimental, have been/are being designed with toroidal interconnection networks. For a given number of nodes, the torus has a relatively larger diameter, but better cost/performance tradeoffs, such as higher channel bandwidth, and lower node degree, when compared to the hypercube. Thus, the torus is becoming a popular topology for the interconnection network of a high performance parallel computers. In a multicomputer, the resources, such as I/O devices or software packages, are distributed over the networks. The first part of the thesis investigates efficient methods of distributing resources in a torus network. Three classes of placement methods are studied. They are (1) distant-t placement problem: in this case, any non-resource node is at a distance of at most t from some resource nodes, (2) j-adjacency problem: here, a non-resource node is adjacent to at least j resource nodes, and (3) generalized placement problem: a non-resource node must be a distance of at most t from at least j resource nodes. This resource placement technique can be applied to allocating spare processors to provide fault-tolerance in the case of the processor failures. Some efficient spare processor placement methods and reconfiguration schemes in the case of processor failures are also described. In a torus based parallel system, some algorithms give best performance if the data are distributed to processors numbered in Cartesian order; in some other cases, it is better to distribute the data to processors numbered in Gray code order. Since the placement patterns may be changed dynamically, it is essential to find efficient methods of rearranging the data from Gray code order to Cartesian order and vice versa. In the second part of the thesis, some efficient methods for data transfer from Cartesian order to radix order and vice versa are developed. The last part of the thesis gives results on generating edge disjoint Hamiltonian cycles in k-ary n-cubes, hypercubes, and 2D tori. These edge disjoint cycles are quite useful for many communication algorithms

Doctor of Philosophy

dissertationStochastic methods, dense free-form mapping, atlas construction, and total variation are examples of advanced image processing techniques which are robust but computationally demanding. These algorithms often require a large amount of computational power as well as massive memory bandwidth. These requirements used to be ful lled only by supercomputers. The development of heterogeneous parallel subsystems and computation-specialized devices such as Graphic Processing Units (GPUs) has brought the requisite power to commodity hardware, opening up opportunities for scientists to experiment and evaluate the in uence of these techniques on their research and practical applications. However, harnessing the processing power from modern hardware is challenging. The di fferences between multicore parallel processing systems and conventional models are signi ficant, often requiring algorithms and data structures to be redesigned signi ficantly for efficiency. It also demands in-depth knowledge about modern hardware architectures to optimize these implementations, sometimes on a per-architecture basis. The goal of this dissertation is to introduce a solution for this problem based on a 3D image processing framework, using high performance APIs at the core level to utilize parallel processing power of the GPUs. The design of the framework facilitates an efficient application development process, which does not require scientists to have extensive knowledge about GPU systems, and encourages them to harness this power to solve their computationally challenging problems. To present the development of this framework, four main problems are described, and the solutions are discussed and evaluated: (1) essential components of a general 3D image processing library: data structures and algorithms, as well as how to implement these building blocks on the GPU architecture for optimal performance; (2) an implementation of unbiased atlas construction algorithms|an illustration of how to solve a highly complex and computationally expensive algorithm using this framework; (3) an extension of the framework to account for geometry descriptors to solve registration challenges with large scale shape changes and high intensity-contrast di fferences; and (4) an out-of-core streaming model, which enables developers to implement multi-image processing techniques on commodity hardware

Reordering Columns for Smaller Indexes

Column-oriented indexes-such as projection or bitmap indexes-are compressed by run-length encoding to reduce storage and increase speed. Sorting the tables improves compression. On realistic data sets, permuting the columns in the right order before sorting can reduce the number of runs by a factor of two or more. Unfortunately, determining the best column order is NP-hard. For many cases, we prove that the number of runs in table columns is minimized if we sort columns by increasing cardinality. Experimentally, sorting based on Hilbert space-filling curves is poor at minimizing the number of runs.Comment: to appear in Information Science

Residue number system coded differential space-time-frequency coding.

Thesis (Ph.D.)-University of KwaZulu-Natal, Durban, 2007.The rapidly growing need for fast and reliable transmission over a wireless channel motivates the development of communication systems that can support high data rates at low complexity. Achieving reliable communication over a wireless channel is a challenging task largely due to the possibility of multipaths which may lead to intersymbol interference (ISI). Diversity techniques such as time, frequency and space are commonly used to combat multipath fading. Classical diversity techniques use repetition codes such that the information is replicated and transmitted over several channels that are sufficiently spaced. In fading channels, the performance across some diversity branches may be excessively attenuated, making throughput unacceptably small. In principle, more powerful coding techniques can be used to maximize the diversity order. This leads to bandwidth expansion or increased transmission power to accommodate the redundant bits. Hence there is need for coding and modulation schemes that provide low error rate performance in a bandwidth efficient manner. If diversity schemes are combined, more independent dimensions become available for information transfer. The first part of the thesis addresses achieving temporal diversity through employing error correcting coding schemes combined with interleaving. Noncoherent differential modulation does not require explicit knowledge or estimate of the channel, instead the information is encoded in the transitions. This lends itself to the possibility of turbo-like serial concatenation of a standard outer channel encoder with an inner modulation code amenable to noncoherent detection through an interleaver. An iterative approach to joint decoding and demodulation can be realized by exchanging soft information between the decoder and the demodulator. This has been shown to be effective and hold hope for approaching capacity over fast fading channels. However most of these schemes employ low rate convolutional codes as their channel encoders. In this thesis we propose the use of redundant residue number system codes. It is shown that these codes can achieve comparable performance at minimal complexity and high data rates. The second part deals with the possibility of combining several diversity dimensions into a reliable bandwidth efficient communication scheme. Orthogonal frequency division multiplexing (OFDM) has been used to combat multipaths. Combining OFDM with multiple-input multiple-output (MIMO) systems to form MIMO-OFDM not only reduces the complexity by eliminating the need for equalization but also provides large channel capacity and a high diversity potential. Space-time coded OFDM was proposed and shown to be an effective transmission technique for MIMO systems. Spacefrequency coding and space-time-frequency coding were developed out of the need to exploit the frequency diversity due to multipaths. Most of the proposed schemes in the literature maximize frequency diversity predominantly from the frequency-selective nature of the fading channel. In this thesis we propose the use of residue number system as the frequency encoder. It is shown that the proposed space-time-frequency coding scheme can maximize the diversity gains over space, time and frequency domains. The gain of MIMO-OFDM comes at the expense of increased receiver complexity. Furthermore, most of the proposed space-time-frequency coding schemes assume frequency selective block fading channels which is not an ideal assumption for broadband wireless communications. Relatively high mobility in broadband wireless communications systems may result in high Doppler frequency, hence time-selective (rapid) fading. Rapidly changing channel characteristics impedes the channel estimation process and may result in incorrect estimates of the channel coefficients. The last part of the thesis deals with the performance of differential space-time-frequency coding in fast fading channels