Pandas Users Get GPU and Cluster Options for Large Datasets
- Pandas is useful for data analytics but inefficient with large datasets, limiting production use
- Dask DataFrame parallelizes Pandas across machines to handle large data
- Most ML data fits in one machine's memory, so clusters can be excessive
- cuDF runs Pandas on GPUs for parallel computing on a single machine
- cuDF enables fast tabular data processing on GPU to accelerate Pandas like Spark does cluster-wide