\n ## Bar Chart: Goroutine Performance by Core Count ### Overview This is a vertical bar chart comparing the execution time (in seconds) of a computational task across different numbers of concurrent goroutines and processor core counts. The chart demonstrates how performance scales with increased parallelism (goroutines) and hardware resources (cores). ### Components/Axes * **Chart Type:** Grouped bar chart. * **X-Axis:** Labeled **"Goroutines"**. It represents the number of concurrent execution threads. The categories are discrete values: 1, 2, 4, 6, 8, 12, 16, 32, 64. * **Y-Axis:** Labeled **"Seconds"**. It represents the execution time, with a linear scale from 0 to 3000, marked at intervals of 500 (0, 500, 1000, 1500, 2000, 2500, 3000). * **Legend:** Positioned on the right side of the chart. It defines three data series by core count: * **4 cores:** Represented by white bars with a black outline. * **6 cores:** Represented by dark gray, densely dotted bars. * **16 cores:** Represented by light gray, sparsely dotted bars. ### Detailed Analysis The chart shows execution time for each combination of goroutine count and core count. Values are approximate, estimated from the bar heights relative to the y-axis. **Trend Verification:** For all three core configurations, the general trend is that execution time decreases as the number of goroutines increases, showing performance improvement from parallelization. The rate of improvement diminishes at higher goroutine counts. **Data Points (Approximate Seconds):** | Goroutines | 4 cores (White) | 6 cores (Dark Gray) | 16 cores (Light Gray) | | :--- | :--- | :--- | :--- | | **1** | ~2750 | ~1650 | ~1900 | | **2** | ~1600 | ~1050 | ~980 | | **4** | ~1050 | ~500 | ~480 | | **6** | ~1050 | ~400 | ~350 | | **8** | ~1020 | ~400 | ~280 | | **12** | ~1010 | ~390 | ~220 | | **16** | ~1010 | ~380 | ~180 | | **32** | ~1000 | ~380 | ~190 | | **64** | ~990 | ~370 | ~180 | **Spatial Grounding & Component Isolation:** * **Header Region:** Contains the y-axis title "Seconds" and the top of the y-axis scale (3000). * **Main Chart Region:** Contains all grouped bars. The legend is placed in the right margin, outside the main plot area. * **Footer Region:** Contains the x-axis title "Goroutines" and the category labels (1, 2, 4, etc.). * For each x-axis category (e.g., "1"), the three bars are grouped together. The leftmost bar in each group is always "4 cores" (white), the middle is "6 cores" (dark gray), and the rightmost is "16 cores" (light gray), matching the top-to-bottom order in the legend. ### Key Observations 1. **Significant Initial Drop:** The most dramatic performance gains (steepest decline in seconds) occur when moving from 1 to 4 goroutines for all core counts. 2. **Diminishing Returns:** After approximately 8-12 goroutines, the performance curves for each core count flatten considerably. Adding more goroutines beyond this point yields minimal further reduction in execution time. 3. **Core Count Impact:** At every goroutine level, more cores result in lower execution time. The performance gap between 4 cores and 16 cores is substantial. 4. **Anomaly at 1 Goroutine:** The execution time for 16 cores (~1900s) is higher than for 6 cores (~1650s) when using only 1 goroutine. This is counter-intuitive and may indicate overhead in managing more cores for a single-threaded task, or a measurement outlier. 5. **Plateau Levels:** The approximate minimum execution times plateau at: * 4 cores: ~1000 seconds * 6 cores: ~380 seconds * 16 cores: ~180 seconds ### Interpretation This chart illustrates the classic principles of parallel computing scalability. The data suggests the task being measured is highly parallelizable, as evidenced by the strong performance improvement with added goroutines and cores. * **Amdahl's Law in Effect:** The flattening of the curves demonstrates the limit of parallel speedup. The portion of the task that cannot be parallelized (serial overhead) becomes the bottleneck, preventing further time reduction regardless of added concurrency or cores. * **Optimal Concurrency:** For this specific task and hardware, there is an optimal range of concurrency (around 8-12 goroutines) beyond which resource contention or scheduling overhead negates the benefits of more parallel threads. * **Resource Provisioning:** The chart provides a practical guide for resource allocation. If the target execution time is ~400 seconds, using 6 cores with 6+ goroutines is sufficient. To achieve ~200 seconds, 16 cores with 12+ goroutines are required. Using 64 goroutines on 4 cores is inefficient, as it provides no benefit over using 12 goroutines. * **The 1-Goroutine Anomaly:** The higher time for 16 cores at 1 goroutine is a critical observation. It implies that for serial or minimally concurrent workloads, a simpler system (fewer cores) may perform better, likely due to reduced context-switching and coordination overhead. This highlights the importance of matching software concurrency patterns to hardware configuration. **Language:** All text in the image is in English.