The article "Reevaluating Amdahl's Law" by John L. Gustafson from Sandia National Laboratories challenges the traditional understanding of Amdahl's law, which states that the maximum speedup from parallel processing is limited by the fraction of serial work in a problem. The authors present timing results from a 1024-processor system that demonstrate that the assumptions underlying Amdahl's 1967 argument are inappropriate for modern massively parallel computing. They argue that the parallel portion of a program scales linearly with the number of processors, not the problem size, and provide examples of achieving unprecedented speedup factors in practical applications. The authors suggest that speedup should be measured by scaling the problem to the number of processors rather than fixing the problem size, and they expect to extend their success to a broader range of applications.The article "Reevaluating Amdahl's Law" by John L. Gustafson from Sandia National Laboratories challenges the traditional understanding of Amdahl's law, which states that the maximum speedup from parallel processing is limited by the fraction of serial work in a problem. The authors present timing results from a 1024-processor system that demonstrate that the assumptions underlying Amdahl's 1967 argument are inappropriate for modern massively parallel computing. They argue that the parallel portion of a program scales linearly with the number of processors, not the problem size, and provide examples of achieving unprecedented speedup factors in practical applications. The authors suggest that speedup should be measured by scaling the problem to the number of processors rather than fixing the problem size, and they expect to extend their success to a broader range of applications.