quality spectrum thus obtained is published for various generations of GPUs on Video Codec SDK web site. NVIDIA encoding benchmarks use the bitrate savings compared with open source encoders x264 and x265's medium preset output, as a measure of the encoding quality. Therefore, it is important to think of encoding performance at a specific quality. But such usage may not be of much use in practical situations. For example, one can encode a video at blazing fast speed, without any regard to quality and claim extremely high performance, doubling the performance on GPUs with multiple NVENC engines. As anyone familiar with video encoding will know, talking about video encoding performance without any reference to encoding quality is meaningless.

The specifics of this depend on the workload, but should be analyzed using a tool such as GPUView (available as a part of Windows Performance Toolkit).Ī: First of all, it is important to note that the aggregate video encoding performance of GPUs is not solely defined by the raw number of NVENCs on the GPU silicon. Since NVENC can run in parallel to CUDA and graphics workload, it is important to ensure that the NVENC pipeline is kept fed with data and the context switches between NVENC pre-processing (which uses small amount of CUDA bandwidth) and other graphics/CUDA workload are minimized. In addition to the above, the overall encoding latency is also affected by efficient application design (or lack thereof). Running quarter-resolution first pass requires less time than running both passes at full resolution. Naturally, 2-pass requires more time to encode than 1-pass rate control mode. Latency contributed by (b) can be minimized by choosing the correct preset, and rate control mode with correct number of rate control passes. In Video SDK 10.0 and above, setting the tuning info to low-latency or ultra-low-latency will set most of these parameters automatically. Each of these can all be set via NVENCODE API.

structure, no look-ahead and lowest possible VBV buffer for the given bitrate and available channel bandwidth, without giving away too much of encoding quality. Typically, latency in (a) can be minimized by choosing infinite GOP with IPPPP. For a typical end-to-end streaming scenario to incur low latency, it is important to lower both components as much as possible. B-frames, look-ahead, VBV buffering), and (b) Latency due to the processing required to encode the bits using hardware or software. A: Video encoding latency consists of two components: (a) Latency due to encoding algorithm (e.g.

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