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<script>var pyinstrumentHTMLRenderer=function(){"use strict";var is=Object.defineProperty;var ns=(F,ve,Pe)=>ve in F?is(F,ve,{enumerable:!0,configurable:!0,writable:!0,value:Pe}):F[ve]=Pe;var A=(F,ve,Pe)=>ns(F,typeof ve!="symbol"?ve+"":ve,Pe);function F(){}function ve(i){return i()}function Pe(){return Object.create(null)}function oe(i){i.forEach(ve)}function pt(i){return typeof i=="function"}function re(i,e){return i!=i?e==e:i!==e||i&&typeof i=="object"||typeof i=="function"}function ki(i){return Object.keys(i).length===0}function St(i,...e){if(i==null){for(const n of e)n(void 0);return F}const t=i.subscribe(...e);return t.unsubscribe?()=>t.unsubscribe():t}function ge(i,e,t){i.$$.on_destroy.push(St(e,t))}function Ci(i,e,t){return i.set(t),e}function u(i,e){i.appendChild(e)}function S(i,e,t){i.insertBefore(e,t||null)}function L
Ran query=1 in 12.8907s
Ran query=1 in 1.4123s
Ran query=1 in 2.0518s
Ran query=2 in 1.9878s
Ran query=2 in 1.1087s
Ran query=2 in 0.5492s
Ran query=3 in 6.8526s
Ran query=3 in 3.0100s
Ran query=3 in 3.1382s
Ran query=4 in 1.5490s
@TomAugspurger
TomAugspurger / io-test.py
Last active February 19, 2025 15:50
kvikio / moto slow benchmark
"""
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
#!/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
"""
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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<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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@TomAugspurger
TomAugspurger / ids.txt
Created October 23, 2023 15:36
Variable query times
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