After optimizing ML models through various compilation stages, the resulting code requires an efficient execution environment. This is the role of the runtime system. This chapter examines the design and implementation of advanced runtime systems tailored for demanding ML tasks.
We will cover critical runtime responsibilities, including:
Studying these components will provide insight into building and analyzing the systems that bring compiled ML models to life on target hardware.
6.1 Runtime Architecture Overview
6.2 Handling Dynamic Shapes and Sizes
6.3 Efficient Memory Management Strategies
6.4 Asynchronous Execution and Scheduling
6.5 Scheduling for Heterogeneous Systems
6.6 Integrating Custom Operators and Kernels
6.7 Interoperability with ML Frameworks
6.8 Hands-on Practical: Implementing a Simple Allocator
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