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Found 6 papers, 3 papers with code
mlirSynth: Automatic, Retargetable Program Raising in Multi-Level IR using Program Synthesis
MLIR is an emerging compiler infrastructure for modern hardware, but existing programs cannot take advantage of MLIR's high-performance compilation if they are described in lower-level general purpose languages.
SLaDe: A Portable Small Language Model Decompiler for Optimized Assembly
SLaDe is up to 6 times more accurate than Ghidra, a state-of-the-art, industrial-strength decompiler and up to 4 times more accurate than the large language model ChatGPT and generates significantly more readable code than both.
Learning C to x86 Translation: An Experiment in Neural Compilation
Deep learning has had a significant impact on many fields.
TASO: Time and Space Optimization for Memory-Constrained DNN Inference
We optimize the trade-off between execution time and memory consumption by: 1) attempting to minimize execution time across the whole network by selecting data layouts and primitive operations to implement each layer; and 2) allocating an appropriate workspace that reflects the upper bound of memory footprint per layer.
Navigating the Landscape for Real-time Localisation and Mapping for Robotics and Virtual and Augmented Reality
Visual understanding of 3D environments in real-time, at low power, is a huge computational challenge.
Introducing SLAMBench, a performance and accuracy benchmarking methodology for SLAM
Real-time dense computer vision and SLAM offer great potential for a new level of scene modelling, tracking and real environmental interaction for many types of robot, but their high computational requirements mean that use on mass market embedded platforms is challenging.
