Alucardx23
Regular
I have been looking online for ways developers might take advantage of the networked hardware in a cloud gaming server, to make the ray tracing calculations more cost effective. I found some information, but not a lot of details on how it would actually work. Can anyone share some info on how this might work or any other links that describe how it can be done?
"When ray-tracing is distributed across multiple machines on the cloud, server side and thus tapping into massive resources, it can deliver the full blown capacity of ray-tracing rendering in realtime. The constraints studios face when building games are lifted. No longer must they navigate the restrictions of various hardware, making sacrifices when executing their gameplay vision, forced to deliver a compromised version of the original concept."
"Imagine rendering one area in a game for 1,000 players, 1,000 times over. As you can imagine, this is extremely time-intensive and expensive. However, this is where cloud-based ray-tracing outperforms other ray-tracing methods. Aspects can be rendered once for an unlimited amount of people as ray-tracing becomes shared across many players, making it a highly cost-effective option."
https://www.hadean.com/blog/cloud-based-ray-tracing-what-is-it-and-how-does-it-work
"As ray tracing is a highly parallel algorithm, Intel MIC Architecture will help provide big gains in performance by increasing the number of available cores for highly parallel applications in the high performance computing (HPC) market and for datacenters. This leads us to the topic of this paper: bringing together the Intel MIC Architecture along with a cloud‐based gaming model to enable more advanced and realistic image rendering with real‐time ray tracing."
"Distributing tile‐based rendering across all servers. This method splits the task of rendering a ray‐traced image into small tiles (like 32x32 or 64x64 pixels) and assigns them to a specific server. The benefit of this approach is that it has very low latency. The machines will work together to finish this one frame as fast as possible. The drawback is that a smart algorithm is required for accurate load balancing between the servers. Some tiles might be calculated much faster than others (e.g., displaying the sky without any geometry is very fast). Therefore it could happen that all but one of the machines are already done with their work but have to sit idle until the last one is finished. To solve that, there are approaches like task stealing, where an idle thread can grab work from the pipeline of another busy thread, that should perform well."
http://wolfrt.de/pdf/Cloud-based_Ray_Tracing.pdf
"When ray-tracing is distributed across multiple machines on the cloud, server side and thus tapping into massive resources, it can deliver the full blown capacity of ray-tracing rendering in realtime. The constraints studios face when building games are lifted. No longer must they navigate the restrictions of various hardware, making sacrifices when executing their gameplay vision, forced to deliver a compromised version of the original concept."
"Imagine rendering one area in a game for 1,000 players, 1,000 times over. As you can imagine, this is extremely time-intensive and expensive. However, this is where cloud-based ray-tracing outperforms other ray-tracing methods. Aspects can be rendered once for an unlimited amount of people as ray-tracing becomes shared across many players, making it a highly cost-effective option."
https://www.hadean.com/blog/cloud-based-ray-tracing-what-is-it-and-how-does-it-work
"As ray tracing is a highly parallel algorithm, Intel MIC Architecture will help provide big gains in performance by increasing the number of available cores for highly parallel applications in the high performance computing (HPC) market and for datacenters. This leads us to the topic of this paper: bringing together the Intel MIC Architecture along with a cloud‐based gaming model to enable more advanced and realistic image rendering with real‐time ray tracing."
"Distributing tile‐based rendering across all servers. This method splits the task of rendering a ray‐traced image into small tiles (like 32x32 or 64x64 pixels) and assigns them to a specific server. The benefit of this approach is that it has very low latency. The machines will work together to finish this one frame as fast as possible. The drawback is that a smart algorithm is required for accurate load balancing between the servers. Some tiles might be calculated much faster than others (e.g., displaying the sky without any geometry is very fast). Therefore it could happen that all but one of the machines are already done with their work but have to sit idle until the last one is finished. To solve that, there are approaches like task stealing, where an idle thread can grab work from the pipeline of another busy thread, that should perform well."
http://wolfrt.de/pdf/Cloud-based_Ray_Tracing.pdf