List of Figures. List of Tables. Preface. Foreword. 1. Basic Concepts. 2. Evolutionary Algorithm MOP Approaches. 3. MOEA Test Suites. 4. MOEA Testing and Analysis. 5. MOEA Theory and Issues. 3. MOEA Theoretical Issues. 6. Applications. 7. MOEA Parallelization. 8. Multi-Criteria Decision Making. 9. Special Topics. 10. Epilog. Appendix A: MOEA Classification and Technique Analysis. Appendix B: MOPs in the Literature. Appendix C: Ptrue & PFtrue for Selected Numeric MOPs. Appendix D: Ptrue & PFtrue for Side-Constrained MOPs. Appendix E: MOEA Software Availability. Appendix F: MOEA-Related Information. Index. References.

/pdf/evolutionary-algorithms-for-solving-multi-objective-problems-2txxk4mqci.pdf

Evolutionary algorithms for solving multi-objective problems

A new algorithm called Mersenne Twister (MT) is proposed for generating uniform pseudorandom numbers. For a particular choice of parameters, the algorithm provides a super astronomical period of 219937 −1 and 623-dimensional equidistribution up to 32-bit accuracy, while using a working area of only 624 words. This is a new variant of the previously proposed generators, TGFSR, modified so as to admit a Mersenne-prime period. The characteristic polynomial has many terms. The distribution up to v bits accuracy for 1 ≤ v ≤ 32 is also shown to be good. An algorithm is also given that checks the primitivity of the characteristic polynomial of MT with computational complexity O(p2) where p is the degree of the polynomial.We implemented this generator in portable C-code. It passed several stringent statistical tests, including diehard. Its speed is comparable to other modern generators. Its merits are due to the efficient algorithms that are unique to polynomial calculations over the two-element field.

/pdf/mersenne-twister-a-623-dimensionally-equidistributed-uniform-2blcriv47b.pdf

Mersenne twister: a 623-dimensionally equidistributed uniform pseudo-random number generator

Efficient application scheduling is critical for achieving high performance in heterogeneous computing environments. The application scheduling problem has been shown to be NP-complete in general cases as well as in several restricted cases. Because of its key importance, this problem has been extensively studied and various algorithms have been proposed in the literature which are mainly for systems with homogeneous processors. Although there are a few algorithms in the literature for heterogeneous processors, they usually require significantly high scheduling costs and they may not deliver good quality schedules with lower costs. In this paper, we present two novel scheduling algorithms for a bounded number of heterogeneous processors with an objective to simultaneously meet high performance and fast scheduling time, which are called the Heterogeneous Earliest-Finish-Time (HEFT) algorithm and the Critical-Path-on-a-Processor (CPOP) algorithm. The HEFT algorithm selects the task with the highest upward rank value at each step and assigns the selected task to the processor, which minimizes its earliest finish time with an insertion-based approach. On the other hand, the CPOP algorithm uses the summation of upward and downward rank values for prioritizing tasks. Another difference is in the processor selection phase, which schedules the critical tasks onto the processor that minimizes the total execution time of the critical tasks. In order to provide a robust and unbiased comparison with the related work, a parametric graph generator was designed to generate weighted directed acyclic graphs with various characteristics. The comparison study, based on both randomly generated graphs and the graphs of some real applications, shows that our scheduling algorithms significantly surpass previous approaches in terms of both quality and cost of schedules, which are mainly presented with schedule length ratio, speedup, frequency of best results, and average scheduling time metrics.

/pdf/performance-effective-and-low-complexity-task-scheduling-for-51tejcgo0m.pdf

Performance-effective and low-complexity task scheduling for heterogeneous computing

B-trees have become, de facto, a standard for file organization. File indexes of users, dedicated database systems, and general-purpose access methods have all been proposed and nnplemented using B-trees This paper reviews B-trees and shows why they have been so successful It discusses the major variations of the B-tree, especially the B+-tree, contrasting the relatwe merits and costs of each implementatmn. It illustrates a general purpose access method whmh uses a B-tree.

http://people.cs.aau.dk/~simas/aalg06/UbiquitBtree.pdf

Ubiquitous B-Tree

https://www.engr.colostate.edu/~hj/journals/71.pdf

A Comparison of Eleven Static Heuristics for Mapping a Class of Independent Tasks onto Heterogeneous Distributed Computing Systems

Scheduling parallel program tasks onto arbitrary target machines

1. Resource Allocation: A Classical Problem. 2. The General Model. 3. Optimal Scheduling Algorithms. 4. The Relationship Between Matching and Two-Processor Scheduling. 5. Static Scheduling Heuristics. 6. SPMD Model. 7. Dynamic Task Allocation. 8. Loop Scheduling on Shared-Memory Computers. 9. Loop Scheduling on Distributed-Memory Computers. 10. Task Partitioning and Grain Size. 11. Scheduling CASE Tools. Appendix. Index.

Task scheduling in parallel and distributed systems

Preface. About the Author. 1. Strategy. 2. Origins. 3. Challenges. 4. Networks. 5. Vulnerability Analysis. 6. Risk Analysis. 7. Water. 8. SCADA. 9. Power. 10. Energy. 11. Telecommunications. 12. Internet. 13. Cyber-Threats. 14. Cyber-Security.

/pdf/critical-infrastructure-protection-in-homeland-security-4krp31mn3w.pdf

Critical Infrastructure Protection in Homeland Security: Defending a Networked Nation

A method called grain packing is proposed as a way to optimize parallel programs. A grain is defined as one or more concurrently executing program modules. A grain begins executing as soon as all of its inputs are available, and terminates only after all of its outputs have been computed. Grain packing reduces total execution time by balancing execution time and communication time. Used with an optimizing scheduler, it gives consistently better results than human-engineered scheduling and packing. The method is language-independent and is applicable to both extended serial and concurrent programming languages, including Occam, Fortran, and Pascal. >

Grain size determination for parallel processing

The generalized feedback shift register pseudorandom number algorithm has several advantages over all other pseudorandom number generators. These advantages are: (1) it produces multidimensional pseudorandom numbers; (2) it has an arbitrarily long period independent of the word size of the computer on which it is implemented; (3) it is faster than other pseudorandom number generators; (4) the “same” floating-point pseudorandom number sequence is obtained on any machine, that is, the high order mantissa bits of each pseudorandom number agree on all machines— examples are given for IBM 360, Sperry-Rand-Univac 1108, Control Data 6000, and Hewlett-Packard 2100 series computers; (5) it can be coded in compiler languages (it is portable); (6) the algorithm is easily implemented in microcode and has been programmed for an Interdata computer.

Ted G. Lewis

Papers

Scheduling parallel program tasks onto arbitrary target machines

Task scheduling in parallel and distributed systems

Critical Infrastructure Protection in Homeland Security: Defending a Networked Nation

Grain size determination for parallel processing

Generalized Feedback Shift Register Pseudorandom Number Algorithm