Implementing OpenMP Offload Support in the AMD Next Generation Fortran Compiler
Bibliographic record
Abstract
Modern-day supercomputers are massively parallel, heterogeneous systems, many of which employ graphics processing units (GPUs) to accelerate applications. While C/C++, and also Python, gain traction in the high-performance computing (HPC) domain, Fortran continues to have a large developer base with new high-performance code written every day. The OpenMP application programming interface (API) is a key ingredient to provide multithreading and support for offloading execution to GPUs for HPC applications. To meet this need, AMD is developing the AMD Next Generation Fortran compiler (“AMD Flang”) to replace the existing “Classic Flang” compiler in the ROCm™ 7.0 release. This paper describes the general compilation pipeline of the AMD Next Generation Fortran Compiler. It shows how the compiler generates code for OpenMP target directives and their map clauses. The paper closes with a discussion of transformations in intermediate representation, such as implementing DO CONCURRENT using OpenMP intermediate code.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".