A comprehensive analysis of power consumption and resources utilization in open-source and proprietary media players
Bibliographic record
Abstract
The growing demand for high-quality media consumption has highlighted the importance of energy-efficient software, particularly media players that handle high-resolution video content. As public is concerned around environmental sustainability and energy use, evaluating the power consumption of software applications has become crucial. This thesis investigates the comparative energy efficiency of open-source and proprietary media players, with a focus on CPU, GPU, and memory consumption during high-resolution video playback. By analyzing resource usage across different platforms, this research aims to provide insights into how software architecture, codec support, and hardware acceleration affect the overall energy consumption of these media players. Open-source media players, such as VLC and MPV, are widely adopted due to their flexibility, cost-effectiveness, and support for a wide range of media formats. However, these players often rely heavily on CPU resources, particularly when hardware acceleration is not fully optimized. This can result in higher power consumption during high-demand tasks such as 4K video playback, especially on platforms where driver support for hardware acceleration is limited. Despite this, open-source players can be energy-efficient when optimized codecs like VP9 and AV1 are used, reducing file sizes and overall power consumption. Proprietary media players, including GOM Player and Windows Media Player, generally outperform their open-source counterparts in terms of energy use. These players benefit from close integration with hardware manufacturers, which allows for better utilization of hardware acceleration and more efficient resource management. Proprietary codecs such as H.264 and H.265 are optimized for energy savings by offloading video processing to the GPU, leading to lower CPU usage and reduced power consumption. The structured support and regular updates that come with proprietary software ensure that these players remain well-optimized for performance and energy efficiency over time. The study utilized real-time power consumption monitoring tools, including HWiNFO and PowerTOP, to assess the performance of both open-source and proprietary media players during high-definition video playback. Metrics such as CPU and GPU power consumption, memory usage, and overall system resource utilization were analyzed in various playback scenarios. The results indicate that proprietary media players typically consume less power due to optimized hardware and software integration, while open-source players can achieve competitive efficiency levels with appropriate codec and hardware configurations. In terms of long-term sustainability, proprietary players tend to offer more immediate energy savings, particularly in environments where media playback is frequent. However, open-source media players, with their flexibility and user-driven customization, present opportunities for power savings over time, especially in cost-sensitive environments. This thesis contributes to the understanding of software energy efficiency, providing valuable insights for developers and users aiming to optimize their media playback experience for reduced energy consumption and environmental impact.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".