Open-Source Python-based Deep Learning Compiler: Hidet


Are you ready to dive into the cutting-edge world of deep learning compiler optimization? In this blog post, we’ll explore the fascinating research behind Hidet, an open-source compiler developed by CentML Inc. that is revolutionizing the efficiency of deep learning inference workloads. From task mapping programming paradigms to post-scheduling fusion optimizations, Hidet is setting new standards for performance and tuning times in the realm of deep learning compilation.

A Glimpse into Hidet’s Innovations

Hidet’s journey begins with the recognition of the complexities involved in developing efficient tensor programs for modern accelerators like NVIDIA GPUs and Google TPUs. Unlike traditional compilers, Hidet takes a unique approach by embedding the scheduling process directly into tensor programs through task mappings. This innovative paradigm allows for fine-grained optimizations at a program-statement level, enhancing efficiency and performance.

Fusion Optimization and Performance Gains

One of Hidet’s standout features is its post-scheduling fusion optimization, which automates the fusion process after scheduling. This not only streamlines the optimization process but also reduces the engineering efforts required for operator fusion. In extensive experiments, Hidet has consistently outperformed state-of-the-art DNN inference frameworks, showcasing an average performance improvement of 1.22x and a maximum gain of 1.48x.

Efficiency at its Core

In addition to its superior performance, Hidet is making waves in reducing tuning times significantly. Compared to other compilers, Hidet slashes tuning times by 20x and 11x, demonstrating its efficiency in accelerating the development and deployment of deep learning models. With its focus on task mapping and fusion optimization, Hidet is paving the way for a new era of deep learning compilation tools.

The Future of Deep Learning Compilation

As Hidet continues to evolve, it presents an exciting opportunity for developers seeking to enhance the efficiency and performance of their deep learning models. With its innovative approach and superior results, Hidet is positioned to become a cornerstone in the toolkit of those pushing the boundaries of deep learning model serving. Stay tuned as we uncover more insights and advancements in the dynamic world of deep learning optimization with Hidet.

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