Design and Develop a CUDA engine working along with C/C++ mode in clang-repl

Description

Incremental compilation pipelines process code chunk-by-chunk by building an ever-growing translation unit. Code is then lowered into the LLVM IR and subsequently run by the LLVM JIT. Such a pipeline allows creation of efficient interpreters. The interpreter enables interactive exploration and makes the C++ language more user friendly. The incremental compilation mode is used by the interactive C++ interpreter, Cling, initially developed to enable interactive high-energy physics analysis in a C++ environment.

Our group puts efforts to incorporate and possibly redesign parts of Cling in Clang mainline through a new tool, clang-repl. The project aims to generalize the IncrementalCUDADeviceCompiler of Cling and add this functionality in clang-repl.

Task ideas

There are several foreseen tasks:

Write a detailed request for comment (RFC) document on the design choices and gather feedback from the LLVM community.
Implement the necessary functionality to support existing test cases available here.
Develop clang-repl-based tutorials for the CUDA backend.
Investigate the requirements for supporting a HIP backend.
Present the work at the relevant meetings and conferences.

Technology

C/C++, CUDA

Desirable Skills

Necessary knowledge: C++ programming; data structures and algorithms.
Basic Knowledge of Clang and LLVM
Experience with GPU programming would be an asset.

Expected results

Demonstrate necessary functionality for existing test cases.
Demonstrate a CUDA-executed gradient computed by the Clad automatic differentiation plugin.

Evaluation Task

Interested students please contact the mentors for an evaluation task.

Mentors

Ioana Ifrim (Princeton)
Vassil Vassilev (Princeton)

Additional Information

Difficulty level (low / medium / high): high
Duration: 350 hours
Mentor availability: May-September

Corresponding Project

Compiler-Research

Participating Organizations

princeton