## Bar Chart: Goroutines vs. Execution Time ### Overview The image is a bar chart comparing the execution time (in seconds) of a program using different numbers of goroutines (1, 2, 4, 6, 8, 12, 16, 32, 64) on systems with 4, 6, and 16 cores. The chart shows how the execution time changes as the number of goroutines increases for each core configuration. ### Components/Axes * **X-axis:** Goroutines (1, 2, 4, 6, 8, 12, 16, 32, 64) * **Y-axis:** Seconds (0 to 3000, with increments of 500) * **Legend (Top-Right):** * White with dots: 4 cores * Gray: 6 cores * Dark Gray with dots: 16 cores ### Detailed Analysis **4 Cores (White with dots):** * Trend: Execution time decreases sharply from 1 to 2 goroutines, then decreases more gradually until 4 goroutines, and then remains relatively constant. * 1 Goroutine: ~2750 seconds * 2 Goroutines: ~1600 seconds * 4 Goroutines: ~1050 seconds * 6 Goroutines: ~1050 seconds * 8 Goroutines: ~1050 seconds * 12 Goroutines: ~1050 seconds * 16 Goroutines: ~1050 seconds * 32 Goroutines: ~1050 seconds * 64 Goroutines: ~1000 seconds **6 Cores (Gray):** * Trend: Execution time decreases sharply from 1 to 2 goroutines, then decreases more gradually until 16 goroutines, and then remains relatively constant. * 1 Goroutine: ~1700 seconds * 2 Goroutines: ~1000 seconds * 4 Goroutines: ~500 seconds * 6 Goroutines: ~400 seconds * 8 Goroutines: ~350 seconds * 12 Goroutines: ~300 seconds * 16 Goroutines: ~200 seconds * 32 Goroutines: ~200 seconds * 64 Goroutines: ~200 seconds **16 Cores (Dark Gray with dots):** * Trend: Execution time decreases sharply from 1 to 2 goroutines, then decreases more gradually until 16 goroutines, and then remains relatively constant. * 1 Goroutine: ~1900 seconds * 2 Goroutines: ~950 seconds * 4 Goroutines: ~500 seconds * 6 Goroutines: ~350 seconds * 8 Goroutines: ~400 seconds * 12 Goroutines: ~400 seconds * 16 Goroutines: ~350 seconds * 32 Goroutines: ~400 seconds * 64 Goroutines: ~200 seconds ### Key Observations * For all core configurations, increasing the number of goroutines initially results in a significant reduction in execution time. * The execution time plateaus after a certain number of goroutines, suggesting diminishing returns. * The 6-core configuration generally has the lowest execution time for higher numbers of goroutines. * The 4-core configuration has the highest execution time across all numbers of goroutines. ### Interpretation The data suggests that using goroutines can significantly improve the performance of a program, especially when the number of goroutines is optimized for the number of available cores. The initial decrease in execution time with increasing goroutines indicates that the program can effectively utilize concurrency. However, the plateauing effect suggests that there is an optimal number of goroutines beyond which adding more does not lead to further performance gains, and may even introduce overhead. The 6-core configuration appears to be the most efficient in this scenario, achieving the lowest execution times for a wide range of goroutine counts. This could be due to a better match between the program's concurrency requirements and the available hardware resources on the 6-core system. The 4-core system consistently performs the worst, likely due to its limited ability to handle a large number of concurrent goroutines.

\n ## Bar Chart: Execution Time vs. Goroutines with Varying Core Counts ### Overview This bar chart depicts the relationship between the number of goroutines and the execution time (in seconds) for different core counts (4, 6, and 16). The chart aims to illustrate how performance scales with increasing goroutines and core availability. ### Components/Axes * **X-axis:** "Goroutines" - Represents the number of concurrent goroutines, with markers at 1, 2, 4, 6, 8, 12, 16, 32, and 64. * **Y-axis:** "Seconds" - Represents the execution time in seconds, ranging from 0 to approximately 3000. * **Legend:** Located in the top-right corner, identifies the three data series: * "4 cores" (Light Gray) * "6 cores" (Medium Gray) * "16 cores" (Dark Gray) ### Detailed Analysis The chart consists of nine bars for each core count, representing the execution time for each number of goroutines. **4 Cores (Light Gray):** * 1 Goroutine: Approximately 2750 seconds. * 2 Goroutines: Approximately 1800 seconds. * 4 Goroutines: Approximately 1000 seconds. * 6 Goroutines: Approximately 600 seconds. * 8 Goroutines: Approximately 400 seconds. * 12 Goroutines: Approximately 300 seconds. * 16 Goroutines: Approximately 200 seconds. * 32 Goroutines: Approximately 250 seconds. * 64 Goroutines: Approximately 200 seconds. **6 Cores (Medium Gray):** * 1 Goroutine: Approximately 1700 seconds. * 2 Goroutines: Approximately 950 seconds. * 4 Goroutines: Approximately 600 seconds. * 6 Goroutines: Approximately 400 seconds. * 8 Goroutines: Approximately 300 seconds. * 12 Goroutines: Approximately 250 seconds. * 16 Goroutines: Approximately 200 seconds. * 32 Goroutines: Approximately 200 seconds. * 64 Goroutines: Approximately 150 seconds. **16 Cores (Dark Gray):** * 1 Goroutine: Approximately 1000 seconds. * 2 Goroutines: Approximately 500 seconds. * 4 Goroutines: Approximately 300 seconds. * 6 Goroutines: Approximately 200 seconds. * 8 Goroutines: Approximately 150 seconds. * 12 Goroutines: Approximately 120 seconds. * 16 Goroutines: Approximately 100 seconds. * 32 Goroutines: Approximately 100 seconds. * 64 Goroutines: Approximately 100 seconds. **Trends:** * For all core counts, the execution time generally decreases as the number of goroutines increases up to a certain point. * The 4-core series shows a significant decrease in execution time from 1 to 4 goroutines, then plateaus and even increases slightly at 32 goroutines. * The 6-core series exhibits a similar trend to the 4-core series, but with lower execution times overall. * The 16-core series shows the most consistent decrease in execution time with increasing goroutines, leveling off at 16, 32, and 64 goroutines. ### Key Observations * Increasing the number of cores consistently reduces execution time. * There appears to be an optimal number of goroutines for each core count. Beyond this point, adding more goroutines does not significantly improve performance and can even degrade it (especially noticeable with 4 cores). * The 16-core system demonstrates the best scalability, maintaining relatively low execution times across all goroutine counts. * The 4-core system shows the most pronounced performance degradation beyond a certain number of goroutines, suggesting contention or overhead becomes significant. ### Interpretation The data suggests that utilizing goroutines can improve performance, but the benefits are heavily dependent on the number of available cores. A system with more cores can effectively handle a larger number of concurrent goroutines without significant overhead. The observed plateau and even increase in execution time with higher goroutine counts on the 4-core system likely indicates that the overhead of context switching and synchronization outweighs the benefits of parallelism. The chart demonstrates the importance of balancing concurrency (goroutines) with available resources (cores) to achieve optimal performance. The 16-core system's consistent performance suggests it is well-equipped to handle a high degree of concurrency, while the 4-core system is more limited. This data could be used to inform decisions about resource allocation and application design to maximize efficiency. The leveling off of the 16 core system at 16 goroutines suggests that the application itself may be the limiting factor, rather than the number of cores.

\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.

## Bar Chart: Execution Time by Goroutines and Core Counts ### Overview The chart compares execution time (in seconds) across different numbers of Goroutines (1, 2, 4, 6, 8, 12, 16, 32, 64) for three core configurations: 4 cores (white), 6 cores (gray), and 16 cores (black). Execution time decreases as Goroutines increase, with 16 cores consistently outperforming 4 and 6 cores. ### Components/Axes - **X-axis (Goroutines)**: Labeled "Goroutines" with values: 1, 2, 4, 6, 8, 12, 16, 32, 64. - **Y-axis (Seconds)**: Labeled "Seconds" with a range from 0 to 3000. - **Legend**: Located on the right, with three entries: - 4 cores (white) - 6 cores (gray) - 16 cores (black) ### Detailed Analysis - **Goroutine 1**: - 4 cores: ~2800 seconds - 6 cores: ~1700 seconds - 16 cores: ~1900 seconds - **Goroutine 2**: - 4 cores: ~1600 seconds - 6 cores: ~1000 seconds - 16 cores: ~950 seconds - **Goroutine 4**: - 4 cores: ~1050 seconds - 6 cores: ~500 seconds - 16 cores: ~480 seconds - **Goroutine 6**: - 4 cores: ~1020 seconds - 6 cores: ~380 seconds - 16 cores: ~320 seconds - **Goroutine 8**: - 4 cores: ~1010 seconds - 6 cores: ~370 seconds - 16 cores: ~280 seconds - **Goroutine 12**: - 4 cores: ~1005 seconds - 6 cores: ~360 seconds - 16 cores: ~240 seconds - **Goroutine 16**: - 4 cores: ~1000 seconds - 6 cores: ~350 seconds - 16 cores: ~220 seconds - **Goroutine 32**: - 4 cores: ~990 seconds - 6 cores: ~340 seconds - 16 cores: ~210 seconds - **Goroutine 64**: - 4 cores: ~980 seconds - 6 cores: ~330 seconds - 16 cores: ~200 seconds ### Key Observations 1. **Inverse Relationship**: Execution time decreases as Goroutines increase for all core configurations. 2. **Core Count Impact**: 16 cores reduce execution time by ~50% compared to 4 cores at Goroutine 1, and by ~60% at Goroutine 64. 3. **Diminishing Returns**: The performance gap between core configurations narrows at higher Goroutine counts (e.g., 4 vs. 16 cores at Goroutine 64: 980 vs. 200 seconds). ### Interpretation The data demonstrates that increasing both Goroutines and core count improves scalability and reduces execution time. The 16-core configuration achieves near-linear speedup with Goroutine growth, suggesting efficient parallelization. The 4-core configuration shows the highest latency, likely due to resource contention. This chart highlights the importance of core allocation in optimizing concurrent workloads, with 16 cores providing the most significant performance gains across all tested scenarios.