Updating the performance comparison slides to use an actual image.

markdown based visual was ugly.

Author: FranciscoThiesen

cppcon2025/cppcon_2025_slides.md

@@ -298,8 +298,10 @@ Player load_player(const std::string& json_str) {
 
 ---
 
+# Benefits
+
 - **No manual field mapping**
-- **No maintenance burden**
+- **No maintenance burden**  
 - **Handles nested structures automatically**
 - **Performance tuned by the library**
 
@@ -918,37 +920,15 @@ _mm512_cmple_epu8_mask(word, _mm512_set1_epi8(31));
 
 # Current JSON Serialization Landscape
 
-**How fast can popular libraries serialize JSON?**
-
-```
-nlohmann::json:     ██                          242 MB/s
-RapidJSON:          █████                       497 MB/s
-Serde (Rust):       █████████████             1,343 MB/s
-yyjson:             ████████████████████      2,074 MB/s
-
-                    0    500   1000  1500  2000  2500  MB/s
-```
+<img src="images/perf_landscape.png" width="85%"/>
 
 ---
 
 # How fast are we? ...
 
-```
-nlohmann::json:     ██                          242 MB/s
-RapidJSON:          █████                       497 MB/s
-Serde (Rust):       █████████████             1,343 MB/s
-yyjson:             ████████████████████      2,074 MB/s
-simdjson:           ██████████████████████████████████ 3,435 MB/s ⭐
+<img src="images/perf_with_simdjson.png" width="80%"/>
 
-                    0    500   1000  1500  2000  2500  3000  3500  MB/s
-```
-
-**3.4 GB/s** on the Twitter benchmark - That's:
-- **14x faster** than nlohmann
-- **2.5x faster** than Rust's Serde
-- **66% faster** than hand-optimized yyjson
-
-**How did we achieve this? Let's find out...**
+**3.4 GB/s** - 14x faster than nlohmann, 2.5x faster than Serde!
 
 ---
 
@@ -1023,7 +1003,6 @@ for (char c : str) {
 }
 ```
 
-<<<<<<< HEAD
 **SIMD (16 bytes at once):**
 ```cpp
 __m128i chunk = load_16_bytes(str);
@@ -1051,49 +1030,22 @@ if (!needs_escape)
 
 **Traditional:**
 ```cpp
-std::to_string(value).length();  // Allocates string just to count digits!
-
-Optimized:
-fast_digit_count(value);  // Bit operations + lookup table, no allocation
-
-| Dataset | Baseline   | No Fast Digits | Impact | Speedup |
-|---------|------------|----------------|--------|---------|
-| Twitter | 3,231 MB/s | 3,041 MB/s     | -6%    | 1.06x   |
-| CITM    | 2,341 MB/s | 1,841 MB/s     | -21%   | 1.27x   |
-
-CITM has ~10,000+ numbers needing digit counts!
-
----
-How Fast Digit Counting Works
-
-The Problem: Need to know buffer size before converting number to string
-
-Traditional Approach:
-```cpp
-size_t digit_count(uint64_t v) {
-    return std::to_string(v).length();
-    // 1. Allocates memory
-    // 2. Converts entire number to string
-    // 3. Gets length
-    // 4. Deallocates string
-}
+std::to_string(value).length();  // Allocates string just to count!
 ```
 
-Our Optimization:
+**Optimized:**
 ```cpp
-int fast_digit_count(uint64_t x) {
-    // Approximate using bit operations (no division!)
-    int y = (19 * int_log2(x) >> 6);
+fast_digit_count(value);  // Bit operations + lookup table
+```
 
-    // Refine using lookup table
-    static uint64_t table[] = {9, 99, 999, 9999, ...};
-    y += x > table[y];
+| Dataset | Baseline | No Fast Digits | **Speedup** |
+|---------|----------|----------------|-------------|
+| Twitter | 3,231 MB/s | 3,041 MB/s | **1.06x** |
+| CITM | 2,341 MB/s | 1,841 MB/s | **1.27x** |
 
-    return y + 1;
-}
-```
+**CITM has ~10,000+ integers!**
 
-Zero allocations, no string conversion, just math!
+---
 
 # Optimizations #4 & #5: Branch Hints & Buffer Growth
 
@@ -1138,16 +1090,7 @@ if (UNLIKELY(buffer_full)) {  // CPU knows this is rare
 
 # Library Performance Comparison
 
-**Twitter Dataset (631KB):**
-```
-simdjson (reflection): ████████████████████████ 3,435 MB/s ⭐
-yyjson:                ██████████████           2,074 MB/s
-Serde (Rust):          █████████                1,343 MB/s
-RapidJSON:             ███                        497 MB/s
-nlohmann::json:        ██                         242 MB/s
-```
-
-**simdjson achieves the fastest JSON serialization performance!**
+<img src="images/perf_comparison.png" width="85%"/>
 
 ---
 

cppcon2025/cppcon_2025_slides_preview.html

@@ -0,0 +1,92 @@
+#!/usr/bin/env python3
+import matplotlib.pyplot as plt
+import numpy as np
+
+# Set up the style
+plt.style.use('default')
+plt.rcParams['figure.facecolor'] = 'white'
+plt.rcParams['axes.facecolor'] = 'white'
+plt.rcParams['font.size'] = 12
+plt.rcParams['font.weight'] = 'bold'
+
+# Data for the charts
+libraries = ['nlohmann::json', 'RapidJSON', 'Serde (Rust)', 'yyjson']
+speeds = [242, 497, 1343, 2074]
+colors = ['#2E86AB', '#A23B72', '#F18F01', '#C73E1D']
+
+# Chart 1: Current Landscape (without simdjson)
+fig, ax = plt.subplots(figsize=(12, 6))
+bars = ax.barh(libraries, speeds, color=colors, height=0.6)
+ax.set_xlabel('Speed (MB/s)', fontsize=14, fontweight='bold')
+ax.set_title('Current JSON Serialization Landscape', fontsize=16, fontweight='bold')
+ax.set_xlim(0, 2500)
+ax.grid(axis='x', alpha=0.3, linestyle='--')
+
+# Add value labels on bars
+for bar, speed in zip(bars, speeds):
+    ax.text(bar.get_width() + 50, bar.get_y() + bar.get_height()/2, 
+            f'{speed} MB/s', va='center', fontweight='bold')
+
+plt.tight_layout()
+plt.savefig('/Users/random_person/Desktop/simdjson_talks/cppcon2025/images/perf_landscape.png', 
+            dpi=150, bbox_inches='tight', facecolor='white')
+plt.close()
+
+# Chart 2: With simdjson reveal
+libraries_with_simdjson = ['nlohmann::json', 'RapidJSON', 'Serde (Rust)', 'yyjson', 'simdjson']
+speeds_with_simdjson = [242, 497, 1343, 2074, 3435]
+colors_with_simdjson = ['#2E86AB', '#A23B72', '#F18F01', '#C73E1D', '#00A878']
+
+fig, ax = plt.subplots(figsize=(14, 6))  # Wider figure
+bars = ax.barh(libraries_with_simdjson, speeds_with_simdjson, color=colors_with_simdjson, height=0.6)
+ax.set_xlabel('Speed (MB/s)', fontsize=14, fontweight='bold')
+ax.set_title('JSON Serialization Performance Comparison', fontsize=16, fontweight='bold')
+ax.set_xlim(0, 4000)  # Extended x-axis limit
+ax.grid(axis='x', alpha=0.3, linestyle='--')
+
+# Add value labels on bars
+for bar, speed, lib in zip(bars, speeds_with_simdjson, libraries_with_simdjson):
+    label = f'{speed} MB/s ⭐' if lib == 'simdjson' else f'{speed} MB/s'
+    ax.text(bar.get_width() + 50, bar.get_y() + bar.get_height()/2, 
+            label, va='center', fontweight='bold')
+
+# Highlight simdjson bar
+bars[-1].set_edgecolor('gold')
+bars[-1].set_linewidth(3)
+
+plt.tight_layout()
+plt.savefig('/Users/random_person/Desktop/simdjson_talks/cppcon2025/images/perf_with_simdjson.png', 
+            dpi=150, bbox_inches='tight', facecolor='white')
+plt.close()
+
+# Chart 3: Final comparison (sorted by performance)
+libraries_sorted = ['simdjson', 'yyjson', 'Serde (Rust)', 'RapidJSON', 'nlohmann::json']
+speeds_sorted = [3435, 2074, 1343, 497, 242]
+colors_sorted = ['#00A878', '#C73E1D', '#F18F01', '#A23B72', '#2E86AB']
+
+fig, ax = plt.subplots(figsize=(14, 6))  # Wider figure
+bars = ax.barh(libraries_sorted, speeds_sorted, color=colors_sorted, height=0.6)
+ax.set_xlabel('Speed (MB/s)', fontsize=14, fontweight='bold')
+ax.set_title('Twitter Dataset (631KB) - Serialization Performance', fontsize=16, fontweight='bold')
+ax.set_xlim(0, 4000)  # Extended x-axis limit
+ax.grid(axis='x', alpha=0.3, linestyle='--')
+
+# Add value labels on bars
+for bar, speed, lib in zip(bars, speeds_sorted, libraries_sorted):
+    label = f'{speed} MB/s ⭐' if lib == 'simdjson' else f'{speed} MB/s'
+    ax.text(bar.get_width() + 50, bar.get_y() + bar.get_height()/2, 
+            label, va='center', fontweight='bold')
+
+# Highlight simdjson bar
+bars[0].set_edgecolor('gold')
+bars[0].set_linewidth(3)
+
+plt.tight_layout()
+plt.savefig('/Users/random_person/Desktop/simdjson_talks/cppcon2025/images/perf_comparison.png', 
+            dpi=150, bbox_inches='tight', facecolor='white')
+plt.close()
+
+print("Charts generated successfully!")
+print("- perf_landscape.png: Current landscape without simdjson")
+print("- perf_with_simdjson.png: Performance comparison with simdjson")
+print("- perf_comparison.png: Final sorted comparison")