Postdoc: Exascale Sparse-Compute Compiler Optimization

1000scholars; Lyon; Sur place; EUR 38 000 - 52 000; Plein temps

Résumé du poste

1000scholars seeks a postdoctoral fellow at the Laboratoire de lInformatique du Parallélisme, ENS Lyon, France, under the PEPR NumPEx program, to address runtime code optimization for sparse computing in HPC and machine learning. The project aims to develop compiler and runtime algorithms to delay specialization of dense code until the sparse structure is known, enabling self-specializing code for sparse inputs.

Validation will use Florida sparse matrix data and ML tasks.

Qualifications

• Notions in compilers, parallelism, parallel architectures, parallel runtimes.
• Experience with C++.
• Languages: English, French.
• Excellent relational skills.

Responsabilités

• Propose code optimizations and data structures for scaling sparse propagation.
• Address runtime scheduling by relying on existing parallel runtimes.
• Validate the complete approach on scientific benchmarks using sparse tensors and ML applications.
• Publish reports and articles.

Connaissances

Compilers

Parallelism

Parallel runtimes

C++

English

French

Algorithms

Description du poste

1000scholars seeks a postdoctoral fellow at the Laboratoire de lInformatique du Parallélisme, ENS Lyon, France, under the PEPR NumPEx program, to address runtime code optimization for sparse computing in HPC and machine learning. The project aims to develop compiler and runtime algorithms to delay specialization of dense code until the sparse structure is known, enabling self-specializing code for sparse inputs.

Validation will use Florida sparse matrix data and ML tasks.