# dendibakh/perf-book

The book "Performance Analysis and Tuning on Modern CPU"

Repository: https://github.com/dendibakh/perf-book
Canonical: https://ross.abutalabs.com/products/perf-book
Homepage: https://products.easyperf.net/perf-book-2
Language: TeX
License: CC0-1.0
License Family: permissive
Last push: 2025-06-09T19:19:54+00:00

## Health v2 (maintenance only)
Score: 34/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 25, release rhythm 8, longevity 100
- inputs: {"age_days": 1731, "days_push": 450, "days_rel": 638, "gap_med": null, "n_releases_24m": 1}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 3631, forks 254 (observed 2026-08-28T04:08:12.037324+00:00)

## What it is
An open-source book titled 'Performance Analysis and Tuning on Modern CPUs' written in TeX and freely licensed under CC0. The repository contains the source for building the PDF, covering how to analyze and optimize software performance on modern CPU architectures.

## Use cases
- learn how to analyze CPU performance bottlenecks
- understand modern CPU microarchitecture for software tuning
- find a free book on performance engineering
- study profiling and performance counters
- optimize hot code paths on x86 CPUs

## When to choose
- you want a free, in-depth resource on CPU performance analysis and tuning
- you are a performance engineer or systems programmer working on low-level optimization
- you want to learn about top-down microarchitecture analysis and hardware counters

## When to avoid
- you need GPU or distributed-systems performance tuning
- you want a hands-on tool rather than a book
- you need beginner-level programming tutorials rather than performance-focused material

## Facets
- artifact type: learning-resource
- maturity: stable
- function: documentation, developer-tools
- domain: performance, developer-tools, tutorials
- platform: windows, cross-platform
- tags: cpu-performance, performance-analysis, book, low-level-optimization, profiling, free-book, linux

## Member repositories
- dendibakh/perf-book (main) score 34

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:08:12.037324+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-29T18:31:52.981230+00:00, confidence not recorded.
  - readme: https://github.com/dendibakh/perf-book (fetched 2026-08-28T04:08:12.037324+00:00, sha d05107738846)
- Data as of 2026-08-30T08:39:29.467469+00:00.