Reducing Kernel Overhead: Managing Tensor Lifecycles in Jeet
Learn how Jeet uses declarative computation graphs to reduce GPU kernel overhead and automate tensor lifecycle management for more efficient ML execution.
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jeetRank Polymorphism Configuration for Multi-Dimensional Array Processing
Array Dimensionality and Rank Control APL employs rank polymorphism to allow a single function to operate across arrays of varying dimensions. While scalar expansion handles basic broadcasting, precise control over the axis of operation is required when applying functions to higher-order tensors without flattening the data structure. The goal is to maintain
apl