Compiler Optimization

Description from the archive archive 2025-07-28.

Benchmarks archive 2025-07-28

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Libraries

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Datasets archive 2025-07-28

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Most implemented papers archive 2025-07-28

11 shown of 11 papers with code (45 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• Compiler Optimization for Quantum Computing Using Reinforcement Learning
  8 Dec 2022 2 repositories listed
  Any quantum computing application, once encoded as a quantum circuit, must be compiled before being executable on a quantum computer.
• EasyTransfer -- A Simple and Scalable Deep Transfer Learning Platform for NLP Applications
  18 Nov 2020 2 repositories listed
  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…
• Compiler Optimization via LLM Reasoning for Efficient Model Serving
  2 Jun 2025 1 repository listed Syntology ran 0 of 6 samples · 6 unverified
  To that end, we introduce a novel compilation framework (dubbed REASONING COMPILER) that formulates optimization as a sequential, context-aware decision process, guided by a large language model and structured Monte…
• Bridging the PLC Binary Analysis Gap: A Cross-Compiler Dataset and Neural Framework for Industrial Control Systems
  27 Feb 2025 1 repository listed
  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…
• Optimization of Armv9 architecture general large language model inference performance based on Llama.cpp
  16 Jun 2024 1 repository listed
  This article optimizes the inference performance of the Qwen-1.
• WhiteFox: White-Box Compiler Fuzzing Empowered by Large Language Models
  24 Oct 2023 1 repository listed Syntology ran 1 of 1 samples · 0 unverified
  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)…
• BaCO: A Fast and Portable Bayesian Compiler Optimization Framework
  1 Dec 2022 1 repository listed Syntology ran 0 of 1 samples · 1 unverified
  We introduce the Bayesian Compiler Optimization framework (BaCO), a general purpose autotuner for modern compilers targeting CPUs, GPUs, and FPGAs.
• SimCLF: A Simple Contrastive Learning Framework for Function-level Binary Embeddings
  6 Sep 2022 1 repository listed
  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…
• Ginex: SSD-enabled Billion-scale Graph Neural Network Training on a Single Machine via Provably Optimal In-memory Caching
  19 Aug 2022 1 repository listed
  Thus, we propose Ginex, the first SSD-based GNN training system that can process billion-scale graph datasets on a single machine.
• CPrune: Compiler-Informed Model Pruning for Efficient Target-Aware DNN Execution
  4 Jul 2022 1 repository listed
  We propose CPrune, a compiler-informed model pruning for efficient target-aware DNN execution to support an application with a required target accuracy.
• CompilerGym: Robust, Performant Compiler Optimization Environments for AI Research
  17 Sep 2021 1 repository listed Syntology ran 1 of 3 samples · 2 unverified
  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…

Syntology lines on 4 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.