CUDA Fortran
E209956
CUDA Fortran is an extension of the Fortran programming language that enables developers to write and run parallel code on NVIDIA GPUs using the CUDA architecture.
All labels observed (3)
| Label | Occurrences |
|---|---|
| CUDA Fortran canonical | 2 |
| NVIDIA HPC Fortran compiler | 1 |
| PGI CUDA Fortran | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T1893369 — resolving that mention is where its identity was fixed. The disambiguator weighed these candidate entities and picked the highlighted one (or “None”, minting a new entity). This is how homonymy is resolved: the same surface form can point to different entities.
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: CUDA Fortran Context triple: [NVIDIA CUDA, supportsLanguage, CUDA Fortran]
-
A.
Fortran
Fortran is a high-level programming language, particularly strong in numerical and scientific computing, widely used for engineering, physics, and high-performance applications.
-
B.
OpenACC
OpenACC is a directive-based parallel programming standard designed to simplify the development of portable, high-performance code on heterogeneous systems such as GPUs and multicore CPUs.
-
C.
NVIDIA CUDA
NVIDIA CUDA is a parallel computing platform and programming model that enables developers to use NVIDIA GPUs for general-purpose high-performance computing.
-
D.
CuPy
CuPy is an open-source array library for Python that accelerates numerical computing by providing a NumPy-compatible interface backed by GPU execution.
-
E.
OpenMP
OpenMP is an application programming interface that supports multi-platform shared-memory parallel programming in C, C++, and Fortran.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: CUDA Fortran Target entity description: CUDA Fortran is an extension of the Fortran programming language that enables developers to write and run parallel code on NVIDIA GPUs using the CUDA architecture.
-
A.
Fortran
Fortran is a high-level programming language, particularly strong in numerical and scientific computing, widely used for engineering, physics, and high-performance applications.
-
B.
OpenACC
OpenACC is a directive-based parallel programming standard designed to simplify the development of portable, high-performance code on heterogeneous systems such as GPUs and multicore CPUs.
-
C.
NVIDIA CUDA
NVIDIA CUDA is a parallel computing platform and programming model that enables developers to use NVIDIA GPUs for general-purpose high-performance computing.
-
D.
CuPy
CuPy is an open-source array library for Python that accelerates numerical computing by providing a NumPy-compatible interface backed by GPU execution.
-
E.
OpenMP
OpenMP is an application programming interface that supports multi-platform shared-memory parallel programming in C, C++, and Fortran.
- F. None of above. chosen
Statements (53)
| Predicate | Object |
|---|---|
| instanceOf |
Fortran extension
ⓘ
GPU programming model ⓘ parallel programming language extension ⓘ |
| basedOn | Fortran ⓘ |
| compatibleWith |
Fortran 2003
ⓘ
linked to:
Fortran
Fortran 90 ⓘ
linked to:
Fortran
Fortran 95 ⓘ
linked to:
Fortran
|
| developedBy |
NVIDIA
ⓘ
linked to:
NVIDIA Corporation
NVIDIA HPC SDK team ⓘ PGI ⓘ |
| documentationURL | https://docs.nvidia.com/hpc-sdk/compilers/cuda-fortran-prog-guide/index.html ⓘ |
| hasFeature |
Fortran array syntax on device data
ⓘ
Fortran syntax for CUDA kernels ⓘ attributes(constant) ⓘ attributes(device) ⓘ attributes(global) ⓘ attributes(host) ⓘ attributes(shared) ⓘ automatic data movement directives ⓘ device variables ⓘ module-based organization ⓘ |
| implementedIn |
NVIDIA HPC SDK
ⓘ
PGI compilers ⓘ |
| languageParadigm |
parallel programming
ⓘ
procedural programming ⓘ |
| requires |
CUDA driver
ⓘ
linked to:
CUDA Driver API
CUDA runtime ⓘ
linked to:
NVIDIA CUDA
CUDA-capable NVIDIA GPU ⓘ |
| supports |
CUDA events
ⓘ
CUDA libraries ⓘ SIMT execution model ⓘ Thrust interoperability ⓘ asynchronous execution ⓘ constant memory ⓘ cuBLAS ⓘ cuFFT ⓘ cuSPARSE ⓘ data-parallel programming ⓘ kernel-based programming ⓘ multi-GPU programming ⓘ shared memory ⓘ streams ⓘ texture memory ⓘ unified memory ⓘ |
| targets |
NVIDIA GPUs
ⓘ
linked to:
Nvidia Maxwell GPU
|
| usedFor |
climate modeling
ⓘ
computational fluid dynamics ⓘ engineering simulations ⓘ high-performance computing ⓘ numerical linear algebra ⓘ physics simulations ⓘ scientific computing ⓘ |
| usesArchitecture |
CUDA
ⓘ
linked to:
NVIDIA CUDA
|
How these facts were elicited
The pipeline generated the facts above by prompting gpt-5.1 with this entity's name + description and the instruction below.
Instruction
You are a knowledge base construction expert. Given a subject entity and a description of it, return factual statements that you know for the subject as a JSON list of dictionaries(triples), where keys must be "subject", "predicate" and "object". The number of facts may be very high, between 25 to 50 or more, for very popular subjects. For less popular subjects, the number of facts can be very low, like 5 or 10. # Requirements - If you don't know the subject at all, return an empty list. - If the subject is not a named entity, return an empty list. - Include at least one triple where predicate is "instanceOf". - Do not get too wordy. - Separate several objects into multiple triples with one object.
Input
Subject: CUDA Fortran Description of subject: CUDA Fortran is an extension of the Fortran programming language that enables developers to write and run parallel code on NVIDIA GPUs using the CUDA architecture.
Referenced by (4)
Full triples — surface form annotated when it differs from this entity's canonical label.