lmcinnes/umap

Create a benchmark to track speed improvements / regressions

Open

#293 建立於 2019年9月11日

在 GitHub 查看
 (8 留言) (0 反應) (0 負責人)Python (6,478 star) (751 fork)batch import
help wanted

描述

Considering a lot of time goes into optimizing the speed of UMAP it seems necessary to have some kind of bechmark/suite to evaluate performance.

EDIT: A collection of useful links to get started: Tracking System Capabilities: https://github.com/giampaolo/psutil Datasets: https://www.tensorflow.org/datasets Benchmarking: https://pypi.org/project/pyperf/

貢獻者指南

技術棧
python
領域
performancedatabackend
議題類型
feature
難度面向新貢獻者的預計實作難度，1 表示很小改動，5 表示專家級工作。
3
預計時間有經驗貢獻者完成調查、實作、測試並準備 pull request 的粗略時間範圍。
1-2 days
活動狀態議題目前的可參與程度：新鮮、活躍、陳舊、阻塞或等待維護者輸入。
stale
清晰度議題是否清楚說明預期改動、驗收標準和下一步。
mostly clear
前置要求
Pythonbenchmarkingperformance testing
新手友善度1-100 的估計分數，表示該議題對首次貢獻者的友善程度。
60
研究方向
Investigate how to set up a benchmark suite for UMAP using pyperf (https://pypi.org/project/pyperf/). Consider using TensorFlow datasets (https://www.tensorflow.org/datasets) for standardized datasets and psutil (https://github.com/giampaolo/psutil) for tracking system capabilities. Look at the existing codebase to identify key performance sensitive areas (e.g., nearest neighbor search, optimization routines) and design benchmarks that measure speed improvements or regressions in those components.
Create a benchmark to track speed improvements / regressions · lmcinnes/umap#293 | Good First Issue