GPU-Accelerated Video Encoding - Nvidia

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GPU Encoding Use Cases • The use cases differ in the way input video frames appear in GPU memory • Frames come from GPU memory when: – Compressing rendered scenes – Transcoding using CUDA decoder • Frames come from CPU memory when: – Encoding/Transcoding of a video file decoded on CPU – Live feed from a webcam or any other video input device via USB 13 PRESENTED BY
GPU Encoding Use Cases Helper libraries for source acquisition acceleration: • NVCUVID – GPU acceleration of H.264, VC-1, MPEG2 decoding in hardware (available in CUDA C SDK) • videoInput – an open-source library for video devices handling on CPU via DirectShow – DirectShow filter can be implemented instead to minimize the amount of “hidden” buffers on the CPU. The webcam filter writes frames directly into pinned/mapped CUDA memory 14 PRESENTED BY
Page 1 and 2: GPU-Accelerated Video Encoding NVID
Page 3 and 4: Outline • Motivation • Video en
Page 5 and 6: Trends • GPU encoding is gaining
Page 11 and 12: Hybrid CPU-GPU encoding pipeline
Page 13: GPU Encoding Use Cases • Video en
Page 17 and 18: Algorithm primitives • Fundamenta
Page 19 and 20: Reduce • Use half of N threads
Page 21 and 22: Reduce sample: 8 numbers 5 14 9 5 2
Page 23 and 24: Reduce sample: 8 numbers 33 14 19 5
Page 25 and 26: Scan sample: 8 numbers 2 9 5 1 3 6
Page 31 and 32: Compact • Having a vector of numb
Page 33 and 34: Compact sample The algorithm makes
Page 35 and 36: Algorithm primitives discussion •
Page 37 and 38: Intra Prediction 36 PRESENTED BY
Page 39 and 40: Intra Prediction • Select the rul
Page 41 and 42: Intra Prediction Plane Constant Ver
Page 43 and 44: CUDA: Intra Prediction 16x16 1. Loa
Page 45 and 46: CUDA: Intra Prediction 16x16 3. __d
Page 47 and 48: CUDA: Intra Prediction 16x16 4. Cal
Page 49 and 50: SAD and SATD • Sum of Absolute Tr
Page 51 and 52: Motion Estimation 50 PRESENTED BY
Page 53 and 54: Motion Estimation 52 PRESENTED BY
Page 55 and 56: Motion Estimation Motion vectors fi
Page 57 and 58: ME - Diamond search • Template me
Page 59 and 60: ME - Candidate Set • Objects that
Page 61 and 62: ME - 3D-wave • 3D-wave treats tim
Page 63 and 64: ME - GPU-friendly candidate set •
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ME - Hierarchical Search Algorithm:
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Outline • Motivation • Video en
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Tesla and Fermi architectures • A
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Multi-GPU encoding • N GOPs for N
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Outline • Motivation • Video en
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Recommended GTC talks We have a ple
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GPU-Accelerated Video Encoding - Nvidia

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