Optimizing Scientific Workloads: Architectural Constraints and Algorithmic Strategies
The efficiency of scientific computing is governed by the synergy between hardware architecture and software implementation. This analysis explores the technical transition from consumer-grade legacy processors (Ivy Bridge and Sandy Bridge microarchitectures) to enterprise-grade server architectures (Broadwell), detailing the implications for instruction sets, virtualization, and cache memory management. Furthermore, it examines strategies for optimizing Fortran code to exploit these architectural distinctives through manual loop tiling and compiler-driven transformations using the Graphite framework.