Benchmark #10

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Automated benchmark at 1722513761

Automated benchmark at 1722513761. See https://github.com/erkexzcx/FlightlessSomething-auto

Submitted 9 months ago by erikas2

Specifications
Label OS GPU CPU RAM OS specific
bpfland-next-c0-t0-k CachyOS AMD Custom GPU 0405 (RADV VANGOGH) AMD Custom APU 0405 16 GB 6.10.2-2-cachyos-deckify-lto schedutil
bpfland-next-defaults CachyOS AMD Custom GPU 0405 (RADV VANGOGH) AMD Custom APU 0405 16 GB 6.10.2-2-cachyos-deckify-lto schedutil
<think> Okay, I'm looking at these two sets of performance metrics for the same benchmark title but from different runs or perhaps different configurations. My goal is to understand how they compare and what insights can be drawn from them. Starting with the first set, labeled as "Title: [Your title here]", it has various metrics like CPU load, GPU load, temperatures, clock speeds, VRAM usage, power consumption, and memory usage. The second set seems similar but perhaps represents a different scenario or after some optimizations were made. Looking at the CPU load, the first set shows a mean of 78.18% with a median of 78.20%, while the second has a slightly lower mean of 78.18% and a median of 78.19%. The standard deviations are almost identical, so the variability in CPU load is similar in both cases. This suggests that the CPU usage is fairly consistent between the two runs. For GPU load, the first set has a mean of 90.95%, median of 92%, and the second also around 90.95% with a median of 92%. The standard deviation in the first set is slightly higher (5.18%) compared to the second (5.17%), but it's negligible. This indicates that the GPU is heavily utilized in both cases, though perhaps more variable in the first instance. Temperatures are another point of comparison. CPU temp in the first run has a mean of 83.02°C with a median of 83°C and a standard deviation of 1.37°C. The second set shows similar numbers: mean 83.02°C, median 83°C, and SD 1.37°C. So temperatures are consistent between the two runs. GPU temp in the first set is around 77.96°C with a median of 78°C and SD 1.04°C. The second set shows slightly higher mean (77.95°C), same median, and similar SD. Not a significant difference here. Clock speeds: GPU core clock in the first set has a mean of 1132.91 MHz with a median of 1158 MHz and a standard deviation of 92.07 MHz. The second set is almost identical: mean 1132.91 MHz, median 1158 MHz, SD 92.07 MHz. So the GPU is operating at similar frequencies in both runs. GPU memory clock is consistently at 687 MHz across both sets with no variation, as indicated by a standard deviation of 0. So that's stable. VRAM usage: The first set has a mean of 0.9207 GB, median 0.9131 GB, and SD 0.01405 GB. The second set is slightly higher at 0.9207 GB with similar median and standard deviation. So VRAM usage is almost the same. GPU power consumption: First set has a mean of 4.23 W, median 4 W, and SD 0.78 W. Second set is identical in these metrics, so no change there. RAM usage: The first set shows RAM used at 7.575 GB on average with a median of 7.576 GB and SD 0.00665 GB. The second set also aligns closely here. Swap usage is around 3.21 GB in both, though the second run has slightly higher maximum. Looking at CPU temperature and load, it's clear that the system is under heavy stress, with CPU temperatures reaching up to 85°C and GPU up to 99°C. This could indicate thermal throttling or potential hardware stress if sustained. The high GPU load suggests that the graphics card is being heavily utilized, which might be expected in a graphically intensive benchmark. However, the CPU load is also quite high at around 78%, indicating that the system is balanced but possibly not optimized for either task. VRAM usage is relatively low, suggesting that the benchmark isn't pushing memory bandwidth to its limits or perhaps it's using lower resolution textures. Swap usage in both runs is around 3.21 GB on average, which might indicate some memory pressure, but it's manageable. I'm noticing that some metrics are identical across both sets, possibly because they were taken under the same conditions or with the same settings. However, there are slight differences in things like swap usage and GPU VRAM usage, which could be due to minor configuration changes or environmental factors. Potential improvements might include optimizing CPU usage to reduce load, ensuring better thermal management to prevent throttling, or adjusting graphics settings to optimize resource utilization. Additionally, monitoring swap usage to prevent potential memory issues could be beneficial. In summary, both runs are performing similarly in terms of processor and GPU activity, with consistent temperatures and power consumption. There's room for optimization but the overall performance is comparable. </think> The two sets of metrics represent similar performance characteristics, indicating consistent system behavior under test conditions. Here's a concise comparison: ### Key Observations: 1. **CPU Load**: Both runs exhibit nearly identical CPU usage (mean ≈ 78.18%), suggesting stable processing demand without significant changes. 2. **GPU Load**: GPU utilization is consistent across both sets, with similar means and medians, indicating steady graphical activity. 3. **Temperatures**: CPU and GPU temperatures remain stable, showing no notable improvement or degradation between runs. 4. **Clock Speeds and Power**: GPU core clock frequencies and power consumption are unchanged, reflecting consistent hardware operation. 5. **Memory Usage**: RAM usage is comparable, with minor variations in swap usage possibly due to configuration differences. ### Potential Areas for Improvement: - **Thermal Management**: Monitor CPU and GPU temperatures to prevent throttling during prolonged use. - **Resource Optimization**: Consider optimizations to reduce peak CPU or GPU loads if thermal constraints are a concern. - **Memory Efficiency**: Review swap usage trends to ensure memory management efficiency. In conclusion, the system's performance is consistent across both runs, with no significant improvements noted. Further optimization could focus on thermal and resource management for sustained high-performance operation.