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""" | |
Sample demonstrating slowness of cudf.read_parquet with kvikio from S3. | |
# Instructions | |
Download the dev wheels (skip if you have it built locally; rquires vpn access) | |
curl -LO https://downloads.rapids.ai/ci/cudf/pull-request/17957/793d0b2/cudf_wheel_python_cudf_cu12_py312_x86_64.tar.gz | |
curl -LO https://downloads.rapids.ai/ci/cudf/pull-request/17957/793d0b2/cudf_wheel_cpp_libcudf_cu12_x86_64.tar.gz |
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#!/usr/bin/env bash | |
set -e | |
PATH=/opt/homebrew/bin:$PATH | |
# The exact UUID doesn't matter, but this should match what you select in the UI. | |
UUID=edef356f-55b1-4132-b311-e5e8c10c6a33 | |
# This path is MacOS specific. | |
OUTPUT=$HOME/Library/Containers/com.microsoft.teams2/Data/Library/Application\ Support/Microsoft/MSTeams/Backgrounds/Uploads |
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""" | |
dali + Zarr (GPU) example. | |
This script adapts the GPU example from | |
https://docs.nvidia.com/deeplearning/dali/user-guide/docs/examples/general/data_loading/external_input.html | |
to use Zarr for storage. | |
To run it, you'll currently need to use my fork of zarr-python: | |
pip install git+https://github.com/TomAugspurger/zarr-python/@tom/fix/gpu |
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""" | |
Test reading (and writing) Zarr data with host and GPU. | |
$ python gputest.py gpu read | |
gpu read 2.96 | |
$ python gputest.py cpu read | |
cpu read 1.24 | |
""" | |
import argparse |
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<!DOCTYPE html> | |
<html lang="en"> | |
<head> | |
<meta charset="utf-8" /> | |
<meta http-equiv="X-UA-Compatible" content="IE=edge" /> | |
<meta name="viewport" content="width=device-width, initial-scale=1" /> | |
<title>memray - flamegraph report (memory leaks)</title> | |
<link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/[email protected]/dist/css/bootstrap.min.css"> |
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S2A_MSIL2A_20210101T000751_R130_T48CWA_20210101T155441 | |
S2A_MSIL2A_20210101T000751_R130_T48CWU_20210605T150149 | |
S2A_MSIL2A_20210101T000751_R130_T50CMC_20210101T155143 | |
S2A_MSIL2A_20210101T000751_R130_T49CDP_20210101T155258 | |
S2A_MSIL2A_20210101T000751_R130_T49CDR_20210101T155234 | |
S2A_MSIL2A_20210101T000751_R130_T49CES_20210101T155247 | |
S2A_MSIL2A_20210101T000751_R130_T48CWV_20210101T155203 | |
S2A_MSIL2A_20210101T000751_R130_T50CMB_20210606T092654 | |
S2A_MSIL2A_20210101T000751_R130_T50CNT_20210101T154951 | |
S2A_MSIL2A_20210101T000751_R130_T49CEP_20210101T155010 |
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import dask.dataframe as dd | |
import adlfs | |
import geopandas | |
import dask_geopandas | |
import pyarrow.fs | |
import pyproj | |
import json | |
import dask.distributed | |
from typing import Dict, Any, Union, Optional |
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