lmcinnes/umap

Create a benchmark to track speed improvements / regressions

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#293 opened on Sep 11, 2019

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 (8 comments) (0 reactions) (0 assignees)Python (6,478 stars) (751 forks)batch import
help wanted

Description

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/

Contributor guide

Tech stack
python
Domain
performancedatabackend
Issue type
feature
DifficultyEstimated implementation difficulty for a new contributor, from 1 for very small changes to 5 for expert-level work.
3
Estimated timeA rough time range for an experienced contributor to investigate, implement, test, and prepare a pull request.
1-2 days
Activity statusHow available the issue appears right now: fresh, active, stale, blocked, or waiting on maintainer input.
stale
ClarityHow clearly the issue explains the expected change, acceptance criteria, and next step.
mostly clear
Prerequisites
Pythonbenchmarkingperformance testing
Newbie friendlinessA 1-100 score estimating how approachable this issue is for first-time contributors.
60
Research direction
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.