👉 Triangle computing is a computational model that leverages the inherent parallelism and locality of operations within triangular data structures, such as triangles in geometry or matrices in linear algebra. In this model, computations are performed by processing elements that are not only adjacent but also have specific angular relationships, typically 120 degrees, which mimics the way certain operations in linear algebra, like matrix multiplication, can be efficiently executed. This approach reduces communication overhead and synchronization costs compared to traditional methods, as operations can be performed locally on neighboring elements without needing global coordination. By exploiting these geometric and algebraic properties, triangle computing offers significant performance improvements for tasks like matrix operations, solving linear systems, and performing fast Fourier transforms, making it a powerful tool in high-performance computing and scientific simulations.
