1m boost for bindi bindi bends the reference rate of every element, so that when it can detect a new bound, its own value is multiplied by the bound reference rate in orde??????r to match. This approach is also known as “soft bounding box”.
This may explain why some of the most widely used bindi techniques can be used to increase performance.
As a result of this approach, we now consider that bindi works well on many of the best GPUs and processors in use in the market today, despite the fact that they do not support it directly.
NVIDIA also supports an alternative solution that is called NVENC. NVIDENT has a similar approach with a hardware-accelerated feature called “fast-pass”.
Our latest results show that NVENC performs better than bindi with the majority of GPUs. In fact, NVIDIA is currently using NVENC on three of its graphics cards.
For AMD GPUs, the most interesting result can be seen with our final GPU results analysis for a single card. AMD is now using NVENC on all its cards and is leading in several ways.
For example, this is what happens with our latest GPU results analysis in our latest testing with four AMD cards using our own fast-pass technique:
NVIDIA and AMD are now competing in many different areas. For many reasons, each company tries to win every market by different methods.
However, when it comes to GPU performance, we can still see clear differences between the GPUs used by each.
The good news is that AMD is starting to move on to the next level, and with the new high-performance Vega GPU with a similar technology – it is becoming competitive with NVIDIA.
All you can do in this case is to keep an eye on this blog for new information about that platform.
Conclusion
As we look for best practices in our GPU performance optimization – how often can we actually make the difference?
Well, that depends on a number of factors. For this situation, there is actually an easy way to predict which technique or approach we have to use, based on our benchmarks. Let’s look at the most important factors to consider in GPU perf??????ormance optimization.
These factors will provid??????e some direction for our overall goal to make the performance increase at least 30% or more.
However, they won’t tell you exactly how effective each technique is in one specific area, for example, performance on the fastest GPUs or on the best GPUs that we tested.
Our GPU performanc