Compiler Optimization
10 papers with code • 0 benchmarks • 0 datasets
Machine learning guided compiler optimization
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Most implemented papers
EasyTransfer -- A Simple and Scalable Deep Transfer Learning Platform for NLP Applications
The literature has witnessed the success of leveraging Pre-trained Language Models (PLMs) and Transfer Learning (TL) algorithms to a wide range of Natural Language Processing (NLP) applications, yet it is not easy to build an easy-to-use and scalable TL toolkit for this purpose.
Compiler Optimization for Quantum Computing Using Reinforcement Learning
Any quantum computing application, once encoded as a quantum circuit, must be compiled before being executable on a quantum computer.
CompilerGym: Robust, Performant Compiler Optimization Environments for AI Research
What is needed is an easy, reusable experimental infrastructure for real world compiler optimization tasks that can serve as a common benchmark for comparing techniques, and as a platform to accelerate progress in the field.
CPrune: Compiler-Informed Model Pruning for Efficient Target-Aware DNN Execution
We propose CPrune, a compiler-informed model pruning for efficient target-aware DNN execution to support an application with a required target accuracy.
Ginex: SSD-enabled Billion-scale Graph Neural Network Training on a Single Machine via Provably Optimal In-memory Caching
Thus, we propose Ginex, the first SSD-based GNN training system that can process billion-scale graph datasets on a single machine.
SimCLF: A Simple Contrastive Learning Framework for Function-level Binary Embeddings
A practical embedding learning framework relies on the robustness of the assembly code representation and the accuracy of function-pair annotation, which is traditionally accomplished using supervised learning-based frameworks.
BaCO: A Fast and Portable Bayesian Compiler Optimization Framework
We introduce the Bayesian Compiler Optimization framework (BaCO), a general purpose autotuner for modern compilers targeting CPUs, GPUs, and FPGAs.
WhiteFox: White-Box Compiler Fuzzing Empowered by Large Language Models
To this end, we propose WhiteFox, the first white-box compiler fuzzer using LLMs with source-code information to test compiler optimization, with a spotlight on detecting deep logic bugs in the deep learning (DL) compilers.
Optimization of Armv9 architecture general large language model inference performance based on Llama.cpp
This article optimizes the inference performance of the Qwen-1. 8B model by performing Int8 quantization, vectorizing some operators in llama. cpp, and modifying the compilation script to improve the compiler optimization level.
Bridging the PLC Binary Analysis Gap: A Cross-Compiler Dataset and Neural Framework for Industrial Control Systems
Industrial Control Systems (ICS) rely heavily on Programmable Logic Controllers (PLCs) to manage critical infrastructure, yet analyzing PLC executables remains challenging due to diverse proprietary compilers and limited access to source code.