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Zarr+CuPy+GDS+nvCOMP made easy (rapidsai#267)
Introducing `open_cupy_array()`, which is a CUDA friendly version of `zarr.open_array` that reads and writes to CuPy arrays. Authors: - Mads R. B. Kristensen (https://github.com/madsbk) Approvers: - Benjamin Zaitlen (https://github.com/quasiben) - Lawrence Mitchell (https://github.com/wence-) URL: rapidsai#267
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# Copyright (c) 2023, NVIDIA CORPORATION. All rights reserved. | ||
# See file LICENSE for terms. | ||
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import cupy | ||
import numpy | ||
import zarr | ||
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import kvikio | ||
import kvikio.zarr | ||
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def main(path): | ||
a = cupy.arange(20) | ||
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# Let's use KvikIO's convenience function `open_cupy_array()` to create | ||
# a new Zarr file on disk. Its semantic is the same as `zarr.open_array()` | ||
# but uses a GDS file store, nvCOMP compression, and CuPy arrays. | ||
z = kvikio.zarr.open_cupy_array(store=path, mode="w", shape=(20,), chunks=(5,)) | ||
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# `z` is a regular Zarr Array that we can write to as usual | ||
z[0:10] = numpy.arange(0, 10) | ||
# but it also support direct reads and writes of CuPy arrays | ||
z[10:20] = cupy.arange(10, 20) | ||
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# Reading `z` returns a CuPy array | ||
assert isinstance(z[:], cupy.ndarray) | ||
assert (a == z[:]).all() | ||
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# Normally, we cannot assume that GPU and CPU compressors are compatible. | ||
# E.g., `open_cupy_array()` uses nvCOMP's Snappy GPU compression by default, | ||
# which, as far as we know, isn’t compatible with any CPU compressor. Thus, | ||
# let’s re-write our Zarr array using a CPU and GPU compatible compressor. | ||
z = kvikio.zarr.open_cupy_array( | ||
store=path, | ||
mode="w", | ||
shape=(20,), | ||
chunks=(5,), | ||
compressor=kvikio.zarr.CompatCompressor.lz4(), | ||
) | ||
z[:] = a | ||
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# Because we are using a CompatCompressor, it is now possible to open the file | ||
# using Zarr's built-in LZ4 decompressor that uses the CPU. | ||
z = zarr.open_array(path) | ||
# `z` is now read as a regular NumPy array | ||
assert isinstance(z[:], numpy.ndarray) | ||
assert (a.get() == z[:]).all() | ||
# and we can write to is as usual | ||
z[:] = numpy.arange(20, 40) | ||
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# And we can read the Zarr file back into a CuPy array. | ||
z = kvikio.zarr.open_cupy_array(store=path, mode="r") | ||
assert isinstance(z[:], cupy.ndarray) | ||
assert (cupy.arange(20, 40) == z[:]).all() | ||
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if __name__ == "__main__": | ||
main("/tmp/zarr-cupy-nvcomp") |
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