Understanding Build Times

One of the most common questions from new Lunar users is: "How long does it take to compile X?" Since Lunar Linux is a source-based distribution, understanding build times helps you plan installations and system updates.

The Short Answer

Build times vary dramatically based on:

• Your hardware (CPU, RAM, disk speed)
• The package being compiled
• System load during compilation
• Compiler optimizations selected

A modern system might compile a complete desktop environment in 2-3 hours, while an older system could take 20+ hours for the same task.

Factors Affecting Build Time

CPU Speed

Double the CPU frequency, and you roughly double compilation speed. A 3 GHz processor compiles approximately twice as fast as a 1.5 GHz processor.

CPU cores matter even more: A quad-core system with parallel builds enabled can be 3-4x faster than a single-core system.

Memory Size

Compilation, especially for C++ applications, requires substantial memory. Memory impact on build speed:

• 128 MB → 512 MB: ~225% faster (2.25x)
• 512 MB → 1 GB: ~50% faster (1.5x)
• 1 GB → 2 GB: ~25% faster (1.25x)

Recommendation: 2 GB minimum for comfortable compilation; 4 GB+ for large packages like browsers and desktop environments.

Disk Speed

I/O operations significantly impact build times, especially for large packages:

• SATA SSD: Fastest (500+ MB/s)
• SATA HDD: Good (100-150 MB/s)
• ATA-133: Moderate (50-100 MB/s)
• ATA-33: Slow (20-30 MB/s)

Modern NVMe SSDs can reduce build times by 20-30% compared to traditional HDDs.

System Idle Time

Every second your system spends on other tasks reduces compilation throughput. For fastest builds:

• Compile on a dedicated system or during low-usage periods
• Minimize interactive applications during compilation
• Disable unnecessary background services

Parallel Make Jobs

Critical for multi-core systems: Enable parallel builds in Lunar:

lunar
# Navigate to: Options → Optimize Architecture
# Set "Number of parallel makes" to your CPU core count

Example impact on quad-core system:

• 1 parallel job: 100% (baseline)
• 2 parallel jobs: ~170% faster
• 4 parallel jobs: ~250-300% faster

Distributed Compilation (distcc)

If you have multiple computers, distcc can distribute compilation across machines, dramatically reducing build times.

Benchmark Data

The following benchmarks are from a Pentium 4 system (circa 2005) running at 2.9 GHz with 1 GB RAM (5864 bogomips):

Note: These are historical reference points. Modern equivalents compile faster on current hardware but may have grown in size and complexity.

Estimating Compilation Time

Rule of Thumb

Based on analysis of 400+ packages, there's a loose correlation between source size and compile time:

Average compilation speed: ~20-25 KB/s of compressed source code

Formula:

Estimated Time (seconds) = Source Size (KB) / 20

Example:

• 10 MB source tarball = 10,000 KB / 20 = 500 seconds = ~8 minutes
• 50 MB source tarball = 50,000 KB / 20 = 2,500 seconds = ~42 minutes

Important: This is a very rough estimate. Actual times can vary by 300% or more depending on the package.

Module Complexity Index

Some packages compile faster or slower than their size suggests. Here are "complexity indices" for common packages (relative to average 1.0):

• gcc: 0.51 (slower than average - bootstrap complexity)
• glibc: 0.31 (slower than average - extensive testing)
• gtk+-2: 0.80 (close to average)
• perl: 1.02 (average)

Multiply your estimate by the complexity index for better accuracy.

Large Package Examples

Modern large packages and estimated times (4-core 3.0 GHz system, 8GB RAM):

• Firefox/Chromium: 30-60 minutes
• LibreOffice: 1-2 hours
• LLVM/Clang: 45-90 minutes
• Qt5: 1-2 hours
• KDE Plasma: 2-4 hours (full desktop)
• GNOME: 2-4 hours (full desktop)

Real-World Installation Times

Time to install a minimal desktop system from Lunar 1.6.5 ISO:

Modern System (2009)

Hardware:

• CPU: 4 cores × 4988 bogomips
• RAM: 6 GB
• Disk: 1681 / 129 MB/s

Installation breakdown:

• ISO install: 11 minutes
• lin gcc glibc gcc bash coreutils tar wget: 1 hour 1 minute
• lin linux-2.6 (kernel): 12 minutes
• lunar update: 20 minutes
• lin XOrg7: 23 minutes
• lin xfce4: 14 minutes
• Total: 2 hours 21 minutes

Legacy System (2000)

Hardware:

• CPU: 1 core × 1600 bogomips
• RAM: 512 MB
• Disk: 179 / 17 MB/s

Installation breakdown:

• ISO install: 18 minutes
• Core system rebuild: 11 hours 26 minutes
• Kernel compilation: 3 hours 37 minutes
• System update: 2 hours 44 minutes
• X11 installation: 3 hours 12 minutes
• Desktop environment: 2 hours 15 minutes
• Total: 23 hours 32 minutes

Conclusion: Avoid installing Lunar on very old hardware unless you have patience or can use distcc.

Optimizing Build Times

Enable Parallel Builds

lunar
# Options → Optimize Architecture → Number of parallel makes
# Set to your CPU core count (check with: nproc)

Use Compiler Cache (ccache)

lin ccache
lunar set CCACHE_DIR=/var/cache/ccache

Ccache can reduce rebuild times by 50-90% for previously compiled code.

Optimize Compilation Flags

Balance speed vs. build time:

• -O2: Best balance (recommended)
• -O3: Slightly faster binaries, 10-20% longer compile
• -Os: Smaller binaries, faster compile

Pre-download Sources

Before starting a large build session:

# Download all sources first
lin --download-only package-name

# Or for complete dependency tree
lin --download-only --deps package-name

This prevents build interruptions from slow downloads.

Tips for Patience

Work Estimation

Before a major system update:

# See what will be rebuilt
lunar update --dry-run

# Check source sizes
ls -lh /var/spool/lunar/

Background Compilation

Run long compilations in screen or tmux so you can disconnect:

screen
lin large-package
# Press Ctrl+A, then D to detach

Overnight Builds

Schedule large compilations for overnight:

# In a screen session
lin kde-full && lin libreoffice && shutdown -h now

Monitoring Build Progress

Watch Compilation

# In another terminal
tail -f /var/log/lunar/compile/module-name*.log

Check System Load

# Monitor CPU and memory
htop

# Check I/O
iotop

Estimated Time Remaining

Unfortunately, Lunar doesn't provide real-time build time estimates. Use the formulas above for rough predictions.

See Also

• Package Management Basics
• System Optimization
• Moonbase Overview