JPEG encoder and decoder library and console application for NVIDIA GPUs for high-performance image encoding and decoding. The software runs also on AMD GPUs using ZLUDA (see ZLUDA.md). This documents provides an introduction to the library and how to use it.

Feb 27, 2025 · The nvJPEG library provides high-performance, GPU accelerated JPEG decoding functionality for image formats commonly used in deep learning and hyperscale multimedia applications.

Builtin parsers for image format detection: jpeg, jpeg2000, tiff, bmp, png, pnm, webp; Python bindings; Zero-copy interfaces to CV-CUDA, PyTorch and CuPy; End-end accelerated sample applications for common image transcoding; Currently there are following native codec extensions: nvjpeg_ext. Hardware jpeg decoder; CUDA jpeg decoder; CUDA ...

The jpeg_gpu project aims to solve both these problems by shifting the decode computation as early as possible to the GPU. Partially decoded JPEG data is uploaded as soon as the entropy coded symbols are read, and a set of pre-defined shaders …

The nvJPEG library is a high-performance GPU-accelerated library for decoding, encoding and transcoding JPEG format images. The nvJPEG2000 library is for decoding JPEG 2000 format images. Applications that rely on nvJPEG or nvJPEG2000 for decoding deliver higher throughput and lower latency compared to CPU-only decoding.

We got ultra fast JPEG compression and decompression on the GPU due to full parallel implementation of Baseline JPEG algorithm. Our CUDA JPEG codec is the fastest in comparison with the best commercial multithreaded JPEG codecs for multicore CPUs. It's also faster than hardware accelerated JPEG codecs. Why JPEG on CUDA could be so fast?

• Decoding JPEG on the CPU has major drawbacks • CPU-based decoding can be unacceptably slow even with partial GPU acceleration • Transferring raw decoded image or intermediate decoding results over PCI-Express is much more expensive •JPEG decoding on the GPU is a perfect solution to both problems

May 23, 2021 · Python interface for nvjpeg. Encode/Decode Jpeg with Nvidia GPU Hardware Acceleration.

Mar 9, 2018 · GPUJPEG is compression and decompression library accelerated on GPU. GPU acceleration allows for compression and decompression of full HD images up to 750fps, 4K images up to 125fps, 8K images up to 33fps on one card.

May 25, 2013 · JPEG is a commonly used method of lossy compression for digital photography (image). This work targets on accelerating JPEG’s compressor and decompressor with GPU. Though the final results are not promising, I would like to introduce the lessons I have learned in accelerating a general system with GPGPU.