Marshall McBride

Papers

Total Citations

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About

Marshall McBride is a researcher whose work bridges evolutionary computing and high-performance computing, focusing on the development of efficient global optimization techniques. His primary research areas include evolutionary algorithms, parallel computing, and the application of PC clusters to solve computationally intensive, non-linear problems. McBride’s major contributions lie in demonstrating how evolutionary computation (EC)—a family of optimization methods inspired by natural selection—can be adapted for high-performance environments. His most-cited paper, "High Performance Evolutionary Computing" (2006, 4 citations), explores how EC techniques, which evolve solutions through selection, recombination, and mutation, can be optimized for speed and scalability. A related work, "High Performance Evolutionary Computation" (2006, 2 citations), addresses the cost and performance challenges that drive HPC communities toward PC clusters, offering practical solutions for implementing EC on accessible hardware. While his citation counts are modest, McBride’s work is notable for its early focus on democratizing high-performance evolutionary computation, making it more accessible to researchers without access to supercomputers. His achievements include pioneering approaches that reduce computational costs while maintaining solution quality, a valuable contribution to the field of optimization.