This Innovation Study introduces the development and testing of an adaptive Conjugate Gradient (aCG) algorithm, a revolutionary solution aimed at mitigating communication and synchronization latencies prevalent in large-scale GPU-based supercomputers. The imperative task of solving vast linear systems, often necessitates iterative methods, such as the Conjugate Gradient (CG) algorithm from the Krylov subspace family. By building upon an adaptive algorithm, aCG diverges from the conventional CPU-controlled standard CG algorithm, addressing host-induced overheads during GPU execution. … Continue reading aCG