These frameworks provide the low-level abstractions needed to execute high-performance parallel computation directly on hardware accelerators. By managing memory hierarchies and kernel execution streams, they enable developers to squeeze maximum throughput out of complex mathematical operations. When evaluating these options, prioritize those that offer mature compiler support for your target architecture and robust libraries for the specific linear algebra primitives your workload requires.

Profile and optimize CUDA code in seconds