How to save the charge of a smartphone?
Since February 23, gentlemen! Yes, the Day of Defender of the Fatherland has long ceased to be only for defenders, but they have a separate salute!
On the occasion of the holiday, we have prepared an article that most guys love - about games. More precisely, about our new development under the code name RAVEN, which will help to save the cherished interest that disappears so quickly when playing on the phone. It renders only those game frames that are noticeably different from those near them. Look under the cat!
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Over the past ten years, mobile games have become a huge industry for the entire gaming industry. According to Newzoo , the global mobile gaming market reached $ 46.1 billion in 2017, which is 19.4% more than a year earlier.
Gamers can enjoy amazing mobile games due to the increasing capabilities of modern mobile graphics processors. However, everything has disadvantages, and in this case - a lot of energy consumption. The power consumption of mobile graphics processors is increasing with an increase in the number of graphics calculations. As a result, high-quality mobile games with advanced graphics are demanding and drain the battery very quickly.
To solve the above problem, researchers from Microsoft Research Asia (MSRA) and the Korea Advanced Institute of Science & Technology (KAIST) have developed a new system called RAVEN, which reduces the power consumption of mobile games without harming the user.
RAVEN is based on FPS in mobile games: many frames that are continuously displayed in the game are either perceived in the same way or very similar. The differences in these frames are too small to be noticeable to the players. However, mobile games always render frames at 60 FPS, no matter how similar they are. Based on the measurement research conducted by scientists, these redundant frames may account for more than 50% of the total number of frames in many games. Obviously, eliminating the rendering of these redundant frames can significantly reduce power consumption.
RAVEN is a new system that relies on a person’s visual perception to scale frame rendering speeds. To achieve this, RAVEN uses perception-aware scaling (PAS) technology. This technique reduces the frame rendering speed in games, when subsequent frames are predicted to be similar to previous ones. At the same time, the similarity should be at that level, so that the user does not notice the "subsidence".
RAVEN uses a side channel to track the displayed frame sequences in order to adapt the user perception of graphics changes during the game. Thus, adjusting RAVEN reduces the power consumption of the GPU.
The RAVEN system consists of three main components that collectively scale the rendering speed of game frames: Track Difference Tracker (F-Tracker), Rate Regulator (R-Regulator), and Rate Injector (R-Injector). All of these components work as a conveyor, in order. First, F-Tracker measures the graphic similarity between two frames. Then R-Regulator predicts the level of similarity between the current and the next frame (frames). Prediction is performed based on how similar the current frame and the previous frame (s) are. If subsequent frames (predicted) are quite similar to the current ones, R-Injector limits the rendering speed of frames by introducing some delay in the rendering cycle and skipping graphic processing for an unnecessary frame (frames). Currently, RAVEN can skip a maximum of up to three frames and, thus, reduce the frame rate to 15 FPS.
The main problem of RAVEN is that it is not clear how to determine the similarity of frames at low cost of computing power. The direct similarity comparison method is the level of structural frame similarity (SSIM). Defining SSIM is a complex calculation and therefore uses more power, especially for wide frames. Today's mobile devices, including smartphones, usually have a high screen resolution of 1920 Ă— 1080 pixels or higher, which makes calculating each SSIM level using RAVEN a pointless exercise.
First , they developed an energy-saving method for measuring graphic similarity based on the susceptibility of the human eye to color difference. This method uses the difference in brightness (that is, the Y component in the YUV color space) between frames. Researchers rated this method positively, comparing it with SSIM under various conditions, and also showed that it effectively measures graphical similarity at low computing power costs.
Second , the researchers built a virtual display that was cloned from the main display of the mobile device, but with a much lower resolution (for example, 80 Ă— 45). The system reads the graphic content of the virtual display to measure the level of similarity. Since the resolution of the virtual display is much smaller, the computational requirements are also much lower.
Thus, the two methods described above effectively reduce the energy consumption of RAVEN.
As a next step, the researchers introduced the RAVEN system into the Nexus 5x smartphone. In a study involving 11 users, colleagues conducted extensive experiments using various gaming applications to evaluate the effectiveness of RAVEN. On average, energy consumption per gaming session decreased by 21.8%, and at a peak by 34.7%. At the same time, the quality and sensations of the game are preserved at the same levels as before the use of RAVEN.
Demonstration on MobiCom 2017:
RAVEN is the first system for mobile games designed to scale the frame rate and save energy, as well as based on the graphic similarity of frames. On MobiCom 2017, the documentation describing the RAVEN “RAVEN: energy optimization for mobile games” system was published and shown. The authors of the technology are Chanyou Hwang, Saumay Pushp, Changyoung Koh, Jungpil Yoon, Seungpyo Choi and Junehwa Song from KAIST and Yunxin Liu from MSRA.
On the occasion of the holiday, we have prepared an article that most guys love - about games. More precisely, about our new development under the code name RAVEN, which will help to save the cherished interest that disappears so quickly when playing on the phone. It renders only those game frames that are noticeably different from those near them. Look under the cat!
')
Over the past ten years, mobile games have become a huge industry for the entire gaming industry. According to Newzoo , the global mobile gaming market reached $ 46.1 billion in 2017, which is 19.4% more than a year earlier.
Gamers can enjoy amazing mobile games due to the increasing capabilities of modern mobile graphics processors. However, everything has disadvantages, and in this case - a lot of energy consumption. The power consumption of mobile graphics processors is increasing with an increase in the number of graphics calculations. As a result, high-quality mobile games with advanced graphics are demanding and drain the battery very quickly.
To solve the above problem, researchers from Microsoft Research Asia (MSRA) and the Korea Advanced Institute of Science & Technology (KAIST) have developed a new system called RAVEN, which reduces the power consumption of mobile games without harming the user.
RAVEN is based on FPS in mobile games: many frames that are continuously displayed in the game are either perceived in the same way or very similar. The differences in these frames are too small to be noticeable to the players. However, mobile games always render frames at 60 FPS, no matter how similar they are. Based on the measurement research conducted by scientists, these redundant frames may account for more than 50% of the total number of frames in many games. Obviously, eliminating the rendering of these redundant frames can significantly reduce power consumption.
RAVEN is a new system that relies on a person’s visual perception to scale frame rendering speeds. To achieve this, RAVEN uses perception-aware scaling (PAS) technology. This technique reduces the frame rendering speed in games, when subsequent frames are predicted to be similar to previous ones. At the same time, the similarity should be at that level, so that the user does not notice the "subsidence".
RAVEN uses a side channel to track the displayed frame sequences in order to adapt the user perception of graphics changes during the game. Thus, adjusting RAVEN reduces the power consumption of the GPU.
The RAVEN system consists of three main components that collectively scale the rendering speed of game frames: Track Difference Tracker (F-Tracker), Rate Regulator (R-Regulator), and Rate Injector (R-Injector). All of these components work as a conveyor, in order. First, F-Tracker measures the graphic similarity between two frames. Then R-Regulator predicts the level of similarity between the current and the next frame (frames). Prediction is performed based on how similar the current frame and the previous frame (s) are. If subsequent frames (predicted) are quite similar to the current ones, R-Injector limits the rendering speed of frames by introducing some delay in the rendering cycle and skipping graphic processing for an unnecessary frame (frames). Currently, RAVEN can skip a maximum of up to three frames and, thus, reduce the frame rate to 15 FPS.
The main problem of RAVEN is that it is not clear how to determine the similarity of frames at low cost of computing power. The direct similarity comparison method is the level of structural frame similarity (SSIM). Defining SSIM is a complex calculation and therefore uses more power, especially for wide frames. Today's mobile devices, including smartphones, usually have a high screen resolution of 1920 Ă— 1080 pixels or higher, which makes calculating each SSIM level using RAVEN a pointless exercise.
To solve this problem, our colleagues used two innovative methods
First , they developed an energy-saving method for measuring graphic similarity based on the susceptibility of the human eye to color difference. This method uses the difference in brightness (that is, the Y component in the YUV color space) between frames. Researchers rated this method positively, comparing it with SSIM under various conditions, and also showed that it effectively measures graphical similarity at low computing power costs.
Second , the researchers built a virtual display that was cloned from the main display of the mobile device, but with a much lower resolution (for example, 80 Ă— 45). The system reads the graphic content of the virtual display to measure the level of similarity. Since the resolution of the virtual display is much smaller, the computational requirements are also much lower.
Thus, the two methods described above effectively reduce the energy consumption of RAVEN.
As a next step, the researchers introduced the RAVEN system into the Nexus 5x smartphone. In a study involving 11 users, colleagues conducted extensive experiments using various gaming applications to evaluate the effectiveness of RAVEN. On average, energy consumption per gaming session decreased by 21.8%, and at a peak by 34.7%. At the same time, the quality and sensations of the game are preserved at the same levels as before the use of RAVEN.
Demonstration on MobiCom 2017:
RAVEN is the first system for mobile games designed to scale the frame rate and save energy, as well as based on the graphic similarity of frames. On MobiCom 2017, the documentation describing the RAVEN “RAVEN: energy optimization for mobile games” system was published and shown. The authors of the technology are Chanyou Hwang, Saumay Pushp, Changyoung Koh, Jungpil Yoon, Seungpyo Choi and Junehwa Song from KAIST and Yunxin Liu from MSRA.
Source: https://habr.com/ru/post/349682/
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