Project 12: Microkernel Performance Benchmarking

Build a benchmarking suite to quantify IPC and context switch overheads.

Quick Reference

Attribute Value
Difficulty Intermediate
Time Estimate 1-2 weeks
Language C (Alternatives: Rust)
Prerequisites IPC basics, timing and profiling
Key Topics rdtsc, microbenchmarks, variance analysis

1. Learning Objectives

By completing this project, you will:

  1. Measure IPC latency with cycle-level precision.
  2. Benchmark context switches and syscall overhead.
  3. Compare multiple OS environments fairly.
  4. Interpret variance and confidence intervals.

2. Theoretical Foundation

2.1 Core Concepts

  • rdtsc / cycle counters: High-resolution timing.
  • Microbenchmarking: Isolate one cost at a time.
  • Warm-up effects: Cache and branch predictors.
  • Statistical variance: Mean vs median vs percentiles.

2.2 Why This Matters

Microkernel debates often hinge on performance. Measuring carefully makes the tradeoffs concrete.

2.3 Historical Context / Background

L4’s performance work showed microkernels can be fast. Modern microkernels (seL4) narrow the gap further.

2.4 Common Misconceptions

  • “One run is enough.” You need multiple runs and statistics.
  • “Raw cycles are universal.” CPU frequency scaling changes results.

3. Project Specification

3.1 What You Will Build

A benchmarking tool that measures IPC round-trip time, context switch overhead, and syscall cost on multiple systems.

3.2 Functional Requirements

  1. Cycle timer: Accurate cycle counter per iteration.
  2. IPC benchmark: Ping-pong between two threads or processes.
  3. Syscall benchmark: Null syscall timing.
  4. Context switch benchmark: Thread switch timing.
  5. Report results: Mean/median/percentiles.

3.3 Non-Functional Requirements

  • Repeatability: Use fixed CPU affinity.
  • Transparency: Report overhead of measurement.
  • Documentation: Include environment details.

3.4 Example Usage / Output

$ ./ipc_bench --iters 100000
IPC round-trip: 420 cycles (median)
Syscall: 120 cycles (median)
Context switch: 800 cycles (median)

3.5 Real World Outcome

$ ./ipc_bench
System: Linux 6.x
IPC (pipe): 2400 cycles
IPC (futex): 1600 cycles
Context switch: 2000 cycles

$ ./ipc_bench --system sel4
IPC (seL4): 400 cycles
Context switch: 500 cycles

4. Solution Architecture

4.1 High-Level Design

┌──────────────┐   ping/pong   ┌──────────────┐
│  Benchmark   │ ───────────▶  │  Worker      │
└──────────────┘ ◀───────────  └──────────────┘
       │
       ▼
  Statistics

4.2 Key Components

Component Responsibility Key Decisions
Timer Cycle counts rdtsc vs clock_gettime
Bench harness Iteration loops warm-up, discard outliers
Stats Mean/median percentiles
Report Output format CSV for comparison

4.3 Data Structures

typedef struct {
    uint64_t *samples;
    size_t count;
} stats_t;

4.4 Algorithm Overview

Key Algorithm: IPC Ping-Pong

  1. Warm up the channel.
  2. Time N iterations of send/receive.
  3. Divide by N and compute stats.

Complexity Analysis:

  • Time: O(N) for N samples
  • Space: O(N) for storing samples

5. Implementation Guide

5.1 Development Environment Setup

cc -O2 -g -o ipc_bench *.c

5.2 Project Structure

bench/
├── src/
│   ├── rdtsc.c
│   ├── ipc_bench.c
│   ├── stats.c
│   └── main.c
└── tests/
    └── test_stats.c

5.3 The Core Question You’re Answering

“What is the true cost of IPC and context switches on modern systems?”

5.4 Concepts You Must Understand First

Stop and research these before coding:

  1. CPU frequency scaling
  2. Affinity and isolation
  3. rdtsc serialization
  4. Statistical measures

5.5 Questions to Guide Your Design

  1. How will you eliminate measurement overhead?
  2. Will you store all samples or only aggregates?
  3. How will you compare systems fairly?

5.6 Thinking Exercise

Estimate Overhead

If rdtsc takes ~30 cycles, how many samples do you need to average that out?

5.7 The Interview Questions They’ll Ask

  1. “How do you benchmark IPC correctly?”
  2. “Why is median often better than mean?”

5.8 Hints in Layers

Hint 1: Use rdtscp It serializes execution more reliably.

Hint 2: Pin threads Avoid scheduler noise with CPU affinity.

Hint 3: Discard first samples Caches and branch predictors need warm-up.

5.9 Books That Will Help

Topic Book Chapter
Performance CS:APP Ch. 5
Benchmarking Systems papers L4 IPC benchmarks

5.10 Implementation Phases

Phase 1: Foundation (3 days)

Goals:

  • Timing primitives

Tasks:

  1. Implement rdtsc/rdtscp helpers.
  2. Validate with a simple loop.

Checkpoint: Timer returns stable values.

Phase 2: Core Functionality (4 days)

Goals:

  • IPC benchmark

Tasks:

  1. Implement ping-pong loop.
  2. Record samples.

Checkpoint: Benchmark outputs mean/median.

Phase 3: Polish & Edge Cases (3 days)

Goals:

  • Cross-system comparison

Tasks:

  1. Add CSV output.
  2. Document system parameters.

Checkpoint: Results are reproducible.

5.11 Key Implementation Decisions

Decision Options Recommendation Rationale
Timer rdtsc, clock_gettime rdtsc Cycle-accurate
Output text, CSV CSV Easier comparison
Statistics mean, median, p95 median + p95 Robust to outliers

6. Testing Strategy

6.1 Test Categories

Category Purpose Examples
Unit Tests Stats correctness median, p95
Integration Tests IPC loop 1000 iterations
Consistency Tests Repeat runs compare variance

6.2 Critical Test Cases

  1. Timer monotonicity is correct.
  2. IPC loop reports plausible cycle counts.
  3. Variance decreases with more samples.

6.3 Test Data

Iterations: 1k, 10k, 100k

7. Common Pitfalls & Debugging

7.1 Frequent Mistakes

Pitfall Symptom Solution
CPU scaling inconsistent results disable scaling, pin cores
Non-serialized rdtsc negative deltas use rdtscp + lfence
Too few samples noisy data increase iterations

7.2 Debugging Strategies

  • Run on isolated core using taskset.
  • Compare with clock_gettime to sanity check.

7.3 Performance Traps

Avoid system calls inside the loop. Collect all samples and process later.

8. Extensions & Challenges

8.1 Beginner Extensions

  • Add a null syscall benchmark.
  • Add histogram output.

8.2 Intermediate Extensions

  • Benchmark page faults.
  • Compare different IPC mechanisms (pipe vs futex).

8.3 Advanced Extensions

  • Compare Linux vs MINIX vs seL4.
  • Publish results with methodology.

9. Real-World Connections

9.1 Industry Applications

  • Performance benchmarking for RTOS validation.
  • Evaluating OS tradeoffs for embedded devices.
  • lmbench: http://www.bitmover.com/lmbench/
  • L4 benchmark papers: referenced in L4 docs.

9.3 Interview Relevance

Performance measurement methodology is a strong systems signal.

10. Resources

10.1 Essential Reading

  • CS:APP - Performance chapters.
  • L4 Microkernels papers - IPC benchmarks.

10.2 Video Resources

  • Performance engineering talks and lectures.

10.3 Tools & Documentation

  • perf: performance counters
  • taskset: CPU affinity
  • Project 1: IPC mechanism.
  • Project 4: Kernel IPC implementation.

11. Self-Assessment Checklist

11.1 Understanding

  • I can explain microbenchmark methodology.
  • I can interpret variance and percentiles.

11.2 Implementation

  • Benchmarks run and produce stable results.
  • Output includes system details.

11.3 Growth

  • I can compare results to published numbers.

12. Submission / Completion Criteria

Minimum Viable Completion:

  • IPC benchmark runs with stable output.
  • Basic stats are reported.

Full Completion:

  • Syscall and context switch benchmarks included.
  • Results repeat within acceptable variance.

Excellence (Going Above & Beyond):

  • Cross-OS comparisons documented.
  • Statistical analysis report included.

This guide was generated from LEARN_MICROKERNELS.md. For the complete learning path, see the parent directory.