Hugging Face Trending Papers

Vectorizer: Vectorizing NumPy Programs with Shape-Guided Rewrite

Vectorizer is a source‑to‑source tool that transforms NumPy programs containing explicit loops into vectorized array operations by rewriting loop bodies from the inside out. It uses array shapes and dataflow analysis to guide a set of rewrite rules that are correct by construction, achieving fast transformations—averaging 0.53 seconds per benchmark. In tests on 150 benchmarks, Vectorizer successfully vectorized 142 directly and 2 with minor edits, producing code that runs on average 74.83× faster than the original loop‑based implementations.

arXiv Machine Learning
Jul 9

VTC: DNN Compilation with Virtual Tensors for Data Movement Elimination

arXiv:2604. 09558v2 Announce Type: replace-cross Abstract: With the widening gap between compute and memory operation latencies, data movement optimizations have become increasingly important for DNN compilation.

By Muyan Hu, Ahan Gupta, Jiachen Yuan, Vima Gupta, Taeksang Kim, Xin Xu, Janardhan Kulkarni, Ofer Dekel, Vikram Adve, Charith Mendis
arXiv Machine Learning
Aug 4

Nova: An End-to-End MLIR Compiler for Deep Learning

arXiv:2608. 00029v1 Announce Type: cross Abstract: The performance of deep learning models at scale relies heavily on how effectively high-level mathematical operations are mapped to underlying physical hardware.

By Adwaid Suresh, Aparna A, Harshini V M, Jona Delcy C A, Killi Uma Maheswara Rao, Ram Charan Golla, Surendra Vendra