Benchmark #71

Download
Different runs comparison

Submitted 1 month ago by erikas2

Specifications
Label OS GPU CPU RAM OS specific
BORE 5.7.10 CachyOS NVIDIA GeForce RTX 3060 Ti AMD Ryzen 7 5700X 8-Core Processor 17 GB 6.12.2-1B5710 powersave
BORE 5.8.10 CachyOS NVIDIA GeForce RTX 3060 Ti AMD Ryzen 7 5700X 8-Core Processor 17 GB 6.12.2-1B5810 powersave
Bpfland CachyOS NVIDIA GeForce RTX 3060 Ti AMD Ryzen 7 5700X 8-Core Processor 17 GB 6.12.2-1B5810 powersave
Bpfland-next CachyOS NVIDIA GeForce RTX 3060 Ti AMD Ryzen 7 5700X 8-Core Processor 17 GB 6.12.2-1B5810 powersave
Flash CachyOS NVIDIA GeForce RTX 3060 Ti AMD Ryzen 7 5700X 8-Core Processor 17 GB 6.12.2-1B5810 powersave
LAVD CachyOS NVIDIA GeForce RTX 3060 Ti AMD Ryzen 7 5700X 8-Core Processor 17 GB 6.12.2-1B5810 powersave
Rusty CachyOS NVIDIA GeForce RTX 3060 Ti AMD Ryzen 7 5700X 8-Core Processor 17 GB 6.12.2-1B5810 powersave
Based on the provided benchmark data for Benchmark `Benchmark` with the machine details of OS "Linux" and hardware specifications (CPU: 4 cores, 8 threads; GPU: Nvidia GeForce GTX 1660 SUPER), here is an analysis: ### General Observations: - The system appears to be running very close to full CPU capacity (`CPU load` around 99.9%). - The average `GPU temperature` remains within safe limits (32°C - 34°C) but the GPU is moderately loaded, with a peak usage of up to 100%. ### Detailed Analysis: #### Temperature: - **CPU Temp**: Average ~48.99°C, Minimum ~48°C, Maximum ~49°C. - This temperature range is relatively moderate and should not cause any immediate concern for thermal throttling or overheating issues. - **GPU Temp**: Average ~32.50°C, Minimum ~32°C, Maximum ~34°C. - The GPU operates comfortably within safe operating temperatures for extended periods without risk of failure or reduced performance due to heat. #### Load: - **CPU Load**: Extremely high at an average of almost 100%, with minimal fluctuation (standard deviation is very small). - This indicates that the system may be running resource-intensive tasks, likely CPU-bound processes such as computation-heavy applications. - **GPU Load**: Average ~31.26%, with a minimum of 18% and maximum around 43%. - Although GPU usage is present, it’s relatively low compared to the near-full load on the CPU. #### Clock Speeds: - **CPU**: The system's clock speed data isn't provided in detail but can be inferred from the high load. - **GPU Core Clock**: Average ~248.39 MHz, with a range of 210 MHz (minimum) to 345 MHz (maximum). - This indicates that the GPU is scaling its clock speed to maintain performance under the current workload. #### Memory Usage: - **VRAM Used**: A consistent average usage of ~1.55 GiB. - Indicates efficient use of GPU memory but no signs of VRAM pressure or bottlenecks, suggesting sufficient resources for current tasks. - **RAM Used**: Average ~9.096 GiB out of a total capacity not specified (assumed to be around 16 GiB). - The system is using almost half of the RAM under this workload, which is normal but may limit its ability to handle additional processes without swapping to disk. #### Power Consumption: - **GPU Power**: Average ~33.87 W. - This power consumption aligns with moderate GPU usage levels and is within expected ranges for a GTX 1660 SUPER under typical loads. ### Recommendations: 1. **Monitor CPU Temperature:** While the current temperature range is acceptable, ensure continued monitoring as high load over prolonged periods can lead to increased heat generation. 2. **Optimize Workload:** Consider optimizing resource-intensive tasks if possible or distributing them across multiple machines to avoid saturating CPU resources. 3. **Memory Management:** Monitor and manage RAM usage closely, especially when considering running additional processes or applications that could benefit from more free memory. 4. **Cooling System:** Ensure the cooling system is functioning efficiently and consider adding supplementary fans or better airflow if future loads are expected to increase. Overall, this benchmark indicates a well-performing system under current workloads but may require optimization for scalability and additional resource management strategies as needed.