Dask-cuDF

E890460

Dask-cuDF is a RAPIDS library that enables distributed, GPU-accelerated DataFrame processing by integrating cuDF with Dask for scalable data analytics.

Try in SPARQL Jump to: Statements Referenced by

Statements (50)

Predicate Object
instanceOf GPU-accelerated data processing framework
Python library
software library
basedOn Dask NERFINISHED
cuDF NERFINISHED
compatibleWith Pandas-like DataFrame API via cuDF
developer NVIDIA NERFINISHED
documentation https://docs.rapids.ai/api/dask-cudf/stable
ecosystem RAPIDS AI ecosystem NERFINISHED
genre data analytics library
dataframe library
distributed computing framework
homepage https://rapids.ai
integratesWith Dask NERFINISHED
RAPIDS cuGraph NERFINISHED
RAPIDS cuML NERFINISHED
cuDF NERFINISHED
license Apache License 2.0
operatingSystem Linux
optimizedFor NVIDIA GPU hardware NERFINISHED
partOf RAPIDS NERFINISHED
programmingLanguage Python
purpose big data processing on GPUs
distributed GPU-accelerated DataFrame processing
scalable data analytics
repository https://github.com/rapidsai/cudf
requires CUDA-capable GPU
Dask NERFINISHED
cuDF NERFINISHED
supportsFeature lazy evaluation
multi-GPU scaling
multi-node distributed execution
out-of-core computation
parallel I/O
task scheduling via Dask
supportsFormat CSV
JSON lines
ORC
Parquet NERFINISHED
supportsLanguage Python
supportsOperation aggregation
filter
groupby
join
window operations
typicalUseCase distributed feature engineering for machine learning
interactive analytics on large tabular datasets
large-scale ETL on GPUs
uses CUDA NERFINISHED
NVIDIA GPUs NERFINISHED

Referenced by (1)

Full triples — surface form annotated when it differs from this entity's canonical label.

NVIDIA RAPIDS component Dask-cuDF