cuDF
E890457
cuDF is a GPU-accelerated DataFrame library from NVIDIA’s RAPIDS ecosystem that enables fast, pandas-like data manipulation and analytics on large datasets.
All labels observed (2)
| Label | Occurrences |
|---|---|
| cuDF canonical | 1 |
| cuDF pandas accelerator | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T10882136 — 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: cuDF Context triple: [NVIDIA RAPIDS, component, cuDF]
-
A.
NVIDIA RAPIDS
NVIDIA RAPIDS is an open-source suite of GPU-accelerated data science and analytics libraries designed to speed up end-to-end machine learning and data processing workflows.
-
B.
Dask
Dask is an open-source parallel computing library for Python that enables scalable, distributed data processing and analytics using familiar interfaces like NumPy, pandas, and scikit-learn.
-
C.
cuDNN
cuDNN is NVIDIA’s GPU-accelerated library of optimized primitives for deep neural networks, widely used to speed up training and inference in frameworks like TensorFlow and PyTorch.
-
D.
cuSOLVER
cuSOLVER is an NVIDIA GPU-accelerated linear algebra library that provides high-performance routines for solving dense and sparse systems of equations, eigenvalue problems, and related numerical tasks.
-
E.
CUDA libraries
CUDA libraries are a collection of NVIDIA-provided GPU-accelerated software libraries that offer optimized routines for tasks such as linear algebra, deep learning, signal processing, and parallel algorithms on CUDA-enabled hardware.
- 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: cuDF Target entity description: cuDF is a GPU-accelerated DataFrame library from NVIDIA’s RAPIDS ecosystem that enables fast, pandas-like data manipulation and analytics on large datasets.
-
A.
NVIDIA RAPIDS
NVIDIA RAPIDS is an open-source suite of GPU-accelerated data science and analytics libraries designed to speed up end-to-end machine learning and data processing workflows.
-
B.
Dask
Dask is an open-source parallel computing library for Python that enables scalable, distributed data processing and analytics using familiar interfaces like NumPy, pandas, and scikit-learn.
-
C.
cuDNN
cuDNN is NVIDIA’s GPU-accelerated library of optimized primitives for deep neural networks, widely used to speed up training and inference in frameworks like TensorFlow and PyTorch.
-
D.
cuSOLVER
cuSOLVER is an NVIDIA GPU-accelerated linear algebra library that provides high-performance routines for solving dense and sparse systems of equations, eigenvalue problems, and related numerical tasks.
-
E.
CUDA libraries
CUDA libraries are a collection of NVIDIA-provided GPU-accelerated software libraries that offer optimized routines for tasks such as linear algebra, deep learning, signal processing, and parallel algorithms on CUDA-enabled hardware.
- F. None of above. chosen
Statements (55)
| Predicate | Object |
|---|---|
| instanceOf |
GPU-accelerated DataFrame library
ⓘ
RAPIDS component ⓘ open-source software ⓘ |
| acceleratedBy | GPU ⓘ |
| compatibleWith |
Apache Spark via RAPIDS Accelerator
NERFINISHED
ⓘ
Dask NERFINISHED ⓘ NumPy NERFINISHED ⓘ RAPIDS cuGraph NERFINISHED ⓘ RAPIDS cuML NERFINISHED ⓘ pandas NERFINISHED ⓘ |
| developer | NVIDIA NERFINISHED ⓘ |
| feature |
GPU-accelerated CSV reading
ⓘ
GPU-accelerated ORC reading ⓘ GPU-accelerated Parquet reading ⓘ columnar memory layout ⓘ out-of-core processing via Dask-cuDF ⓘ pandas-like API ⓘ zero-copy interoperability with other RAPIDS libraries ⓘ |
| introducedBy | RAPIDS open-source announcement in 2018 ⓘ |
| license | Apache License 2.0 ⓘ |
| modeledAfter | pandas NERFINISHED ⓘ |
| partOf |
RAPIDS
NERFINISHED
ⓘ
RAPIDS AI ecosystem NERFINISHED ⓘ |
| programmingLanguage |
C++
ⓘ
CUDA NERFINISHED ⓘ Python ⓘ |
| provides |
DataFrame abstraction
ⓘ
GPU-accelerated columnar data structures ⓘ Series abstraction ⓘ |
| repository | https://github.com/rapidsai/cudf ⓘ |
| requires | NVIDIA GPU NERFINISHED ⓘ |
| supports |
ETL workloads
ⓘ
SQL-like operations ⓘ data analytics ⓘ data manipulation ⓘ tabular data processing ⓘ |
| supportsLanguageBinding |
C++ API
NERFINISHED
ⓘ
Python API ⓘ |
| supportsOperation |
I/O operations
ⓘ
aggregation ⓘ datetime operations ⓘ filtering ⓘ groupby ⓘ join ⓘ missing value handling ⓘ sorting ⓘ string operations ⓘ type casting ⓘ window functions ⓘ |
| useCase |
data science workflows
ⓘ
large-scale data analytics ⓘ machine learning preprocessing ⓘ |
| uses |
Apache Arrow columnar memory format
ⓘ
CUDA parallel computing platform NERFINISHED ⓘ |
| website | https://rapids.ai ⓘ |
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: cuDF Description of subject: cuDF is a GPU-accelerated DataFrame library from NVIDIA’s RAPIDS ecosystem that enables fast, pandas-like data manipulation and analytics on large datasets.
Referenced by (2)
Full triples — surface form annotated when it differs from this entity's canonical label.
this entity surface form:
cuDF pandas accelerator