activity
20222024
most citedLarge Language Models for Compiler Optimization

11 citations · 18 across the 7 of their papers we have counts for

collaborators

7 papers

cs.PL2024

Compiler generated feedback for Large Language Models

Dejan Grubisic, Chris Cummins, Volker Seeker +1

We introduce a novel paradigm in compiler optimization powered by Large Language Models with compiler feedback to optimize the code size of LLVM assembly. The model takes unoptimiz…

cs.LG2024

Priority Sampling of Large Language Models for Compilers

Dejan Grubisic, Chris Cummins, Volker Seeker +1

Large language models show great potential in generating and optimizing code. Widely used sampling methods such as Nucleus Sampling increase the diversity of generation but often p…

cs.SE20245 cited

CRUXEval: A Benchmark for Code Reasoning, Understanding and Execution

Alex Gu, Baptiste Rozière, Hugh Leather +3

We present CRUXEval (Code Reasoning, Understanding, and eXecution Evaluation), a benchmark consisting of 800 Python functions (3-13 lines). Each function comes with an input-output…

cs.PL202311 cited

Large Language Models for Compiler Optimization

Chris Cummins, Volker Seeker, Dejan Grubisic +8

We explore the novel application of Large Language Models to code optimization. We present a 7B-parameter transformer model trained from scratch to optimize LLVM assembly for code…

cs.LG2023

BenchDirect: A Directed Language Model for Compiler Benchmarks

Foivos Tsimpourlas, Pavlos Petoumenos, Min Xu +4

The exponential increase of hardware-software complexity has made it impossible for compiler engineers to find the right optimization heuristics manually. Predictive models have be…

cs.PL20232 cited

Learning Compiler Pass Orders using Coreset and Normalized Value Prediction

Youwei Liang, Kevin Stone, Ali Shameli +8

Finding the optimal pass sequence of compilation can lead to a significant reduction in program size and/or improvement in program efficiency. Prior works on compilation pass order…