NVIDIA Video Codec SDK v12.2 (Latest Release)
NVIDIA Video Codec SDK v12.2 (Latest Release) Download PDF

NVDEC Application Note

NVIDIA GPUs contain a hardware-based decoder (referred to as NVDEC in this document) which provides fully accelerated hardware-based video decoding for several popular codecs. With complete decoding offloaded to NVDEC, the graphics engine and CPU are free for other operations.

NVDEC supports much faster than real-time decoding which makes it suitable for transcoding scenarios in addition to video playback.

The hardware capabilities available in NVDEC are exposed through APIs referred to as NVDECODE APIs in this document. This document provides information about the capabilities of the NVDEC engine and the features exposed through NVDECODE APIs. The current document highlights only the changes in the current video codec SDK package with respect to the previous SDK packages. To know about the features exposed in earlier SDKs please refer to the earlier SDK package(s).

Introduction

NVDEC Capabilities

At a high level, Table 1 summarizes the capabilities of the NVDEC engine exposed through NVDECODE APIs.

Table 1. NVDEC Hardware Capabilities
Hardware Features 1st Gen Maxwell GPUs 2nd Gen Maxwell GPUs Pascal GPUs Volta GPUs Turing/GA100/Hopper GPUs GA10x3 and Ada GPUs
VC1 Simple, Main & Advanced profiles Y Y Y Y Y Y
MPEG4 Simple and Advanced Simple Profiles Y Y Y Y Y Y
MPEG2 Simple & Main profiles Y Y Y Y Y Y
H.264 Baseline, Main, High Profiles Y Y Y Y Y Y
VP8 N Y Y1 Y Y Y
HEVC Main and Main 10 Profile1 N Y1 Y Y Y Y
VP9 Profile 01 N Y1 Y Y Y Y
8192x8192 Decoding support (HEVC&VP9 only) N N Y1 Y Y Y
Multiple NVDECs2 N N N N Y Y
HEVC 444 decoding N N N N Y Y
AV1 Main Profile decoding N N N N N Y

  • Y: Supported, N: Unsupported
  • 1: Present in select GPUs
  • 2: Present in select GPUs
  • 3: GA10x GPUs include all GPUs based on Ampere architecture except GA100

NVDEC Performance

NVDEC natively supports multiple hardware decoding contexts with negligible context-switching penalty. As a result, subject to the hardware performance limit and available memory, an application can decode multiple videos simultaneously.

The hardware and software maintain the context for each decoding session, allowing many simultaneous decoding sessions to run in parallel with minimal context switch penalty. Table 2 provides indicative data of the decoding performance of NVDEC in GPUs based on Maxwell, Pascal, Turing and Ampere architectures for AV1, HEVC, VP9, and H.264 encoded bitstreams. The performance varies across GPU classes (e.g. Quadro, Tesla), and scales (almost) linearly with the clock speeds for each hardware.

Table 2. NVDEC decoding performance (indicative)
GPU Architecture Codec Performance in frames/second
Pascal(GTX1060) H.264 696
VP9 835
HEVC 803
HEVC Main10 787
Turing (RTX8000) H.264 719
VP9 864
VP9 10 bit 871
HEVC 1247
HEVC Main10 1145
Ampere (RTX3090) H.264 742
VP9 1069
VP9 10 bit 1116
HEVC 1419
HEVC Main10 1323
AV1 849
Ada (RTX4090) H.264 883
VP9 1265
VP9 10 bit 1322
HEVC 1666
HEVC Main10 1549
AV1 1005

  • All the measurement is done on the highest video clocks as reported by nvidia-smi (i.e. 1129 MHz, 1683 MHz, 1755 MHz, 1770 MHz for M2000, P2000, RTX8000 and RTX3090 respectively). The performance should scale according to the video clocks as reported by nvidia-smi for other GPUs of every individual family. Information on nvidia-smi can be found at https://developer.nvidia.com/nvidia-system-management-interface .
  • Resolution/Input format: 1920x1080/YUV 4:2:0
  • Software: Windows 11, Video Codec SDK v12.2, NVIDIA display driver: 551.76
  • Hopper and GA100 GPUs contain NVDEC with same architecture as Turing. As a result, the decoding performance on Hopper and GA100 GPUs is same as that of Turing GPUs, scaled by the clock speed. To view the clocks available on your GPU, please use the tool nvidia-smi included with the NVIDIA driver.

While Maxwell, Pascal, and Volta generation GPUs had one NVDEC engine per chip, some GPUs based on Turing, Ampere, Ada and Hopper architecture have multiple NVDEC engines per chip. GH100 has 8 NVDECs. This increases the aggregate decoding throughput of the GPU. The NVIDIA driver takes care of load balancing among multiple NVDEC engines on the chip so that applications don’t require special code to take advantage of multiple decoders, and automatically benefit from higher decoder capacity on higher-end GPU hardware. The decode performance listed in Table 2 is given per NVDEC engine. Thus, if a Quadro or Tesla GPU has 2 NVDECs, multiply the corresponding number in Table 2 by the number of NVDECs per chip to get aggregate maximum performance (applicable only when running multiple simultaneous decode sessions). Note that performance with a single decoding session cannot exceed performance per NVDEC, regardless of the number of NVDECs present on the GPU. All GeForce products consist of a single NVDEC.

Programming NVDEC

Refer to the SDK release notes for information regarding the required driver version.

Various capabilities of NVDEC are exposed to the application software via the NVIDIA proprietary application programming interface (NVDECODE APIs). Refer to the Video Decoder Programming guide for details on using these APIs.

For a complete list of GPUs supporting hardware accelerated decoding refer to https://developer.nvidia.com/nvidia-video-codec-sdk.

FFmpeg Support

FFmpeg is the most popular multimedia transcoding tool used extensively for video and audio transcoding.

The video hardware accelerators in NVIDIA GPUs can be effectively used with FFmpeg to significantly speed up the video decoding, encoding and end-to-end transcoding at very high performance.

Note that FFmpeg is open-source project and its usage is governed by specific licenses and terms and conditions.

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