To extend Allo's composable schedules and holistic dataflow optimizations to support dynamic-sized inputs and outputs, several adjustments and enhancements can be implemented.
Dynamic Memory Allocation: Allo can incorporate mechanisms for dynamic memory allocation to handle varying input and output sizes. By allowing for dynamic resizing of memory buffers based on the input dimensions, Allo can adapt to different data sizes at runtime.
Parameterized Templates: Introducing parameterized templates for kernel designs can enable the creation of flexible designs that can accommodate dynamic input and output sizes. By defining templates with parameters for input and output dimensions, Allo can generate customized designs on-the-fly based on the specific input requirements.
Runtime Configuration: Implementing runtime configuration options within Allo can allow users to specify input and output sizes dynamically during program execution. This runtime flexibility can enable Allo to adjust the hardware design on the fly based on the actual input data dimensions.
Dataflow Analysis: Enhancing Allo's dataflow analysis capabilities to handle variable-sized data streams can ensure efficient data movement and processing. By dynamically optimizing dataflow paths based on the input and output sizes, Allo can maximize performance for varying data dimensions.
By incorporating these features and enhancements, Allo can effectively support dynamic-sized inputs and outputs while maintaining its composable schedules and holistic dataflow optimizations.