When Polyhedral Transformations Meet SIMD Code Generation
Data locality and parallelism are critical optimization objectives for performance on modern multi-core machines. Both coarse-grain parallelism (e.g., multi-core) and fine-grain parallelism (e.g., vector SIMD) must be effectively exploited, but despite decades of progress at both ends, current compiler optimization schemes that attempt to address data locality and both kinds of parallelism often fail at one of the three objectives. The authors address this problem by proposing a 3-step framework, which aims for integrated data locality, multi-core parallelism and SIMD execution of programs.
Subscribe to the Innovation Insider Newsletter
Catch up on the latest tech innovations that are changing the world, including IoT, 5G, the latest about phones, security, smart cities, AI, robotics, and more. Delivered Tuesdays and Fridays