ABSTRACT: Artificial deep neural networks (ADNNs) have become a cornerstone of modern machine learning, but they are not immune to challenges. One of the most significant problems plaguing ADNNs is ...
Abstract: Bosonic quantum computing, based on the infinite-dimensional qumodes, has shown promise for various practical applications that are classically hard. However, the lack of compiler ...
Discover how LLM visibility is reshaping SEO. Learn to track brand mentions in AI responses, new metrics beyond rankings, and optimization strategies for 2025. Generative AI is reshaping how people ...
Deep-learning throughput hinges on how effectively a compiler stack maps tensor programs to GPU execution: thread/block schedules, memory movement, and instruction selection (e.g., Tensor Core MMA ...
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This repository is supplementary to our paper, CompilerDream: Learning a Compiler World Model for General Code Optimization [Arxiv]. We provide the code of our experiments, along with the training ...
The use of graphical language in quantum computing for the representation of algorithms, although intuitive, is not very useful for different tasks such as the description of quantum circuits in text ...
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