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 …

Large Language Models (LLMs) have demonstrated remarkable capabilities across a
variety of software engineering and coding tasks. However, their application in the domain of …

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 …

Code is increasingly becoming a core data modality of modern machine learning research
impacting not only the way we write code with conversational agents like OpenAI's ChatGPT …

Vectorization is a powerful optimization technique that significantly boosts the performance
of high performance computing applications operating on large data arrays. Despite …

Compilers use a wide range of advanced optimizations to improve the quality of the machine
code they generate. In most cases, compiler optimizations rely on precise analyses to be …

Large Language Models (LLMs) have demonstrated remarkable capabilities across a
variety of software engineering and coding tasks. However, their application in the domain of …

With the impact of real-time processing being realized in the recent past, the need for
efficient implementations of reinforcement learning algorithms has been on the rise. Albeit …

Diligent utilization of hardware resources when dealing with computationally intensive jobs
like machine learning (ML) that have a huge scope of compiler optimizations are often …

The key to performance optimization of a program is to decide correctly when a certain
transformation should be applied by a compiler. This is an ideal opportunity to apply …