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Top 13 C++ Inference Projects
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ncnn
ncnn is a high-performance neural network inference framework optimized for the mobile platform
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InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
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TensorRT
NVIDIA® TensorRT™ is an SDK for high-performance deep learning inference on NVIDIA GPUs. This repository contains the open source components of TensorRT.
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jetson-inference
Hello AI World guide to deploying deep-learning inference networks and deep vision primitives with TensorRT and NVIDIA Jetson.
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TNN
TNN: developed by Tencent Youtu Lab and Guangying Lab, a uniform deep learning inference framework for mobile、desktop and server. TNN is distinguished by several outstanding features, including its cross-platform capability, high performance, model compression and code pruning. Based on ncnn and Rapidnet, TNN further strengthens the support and performance optimization for mobile devices, and also draws on the advantages of good extensibility and high performance from existed open source efforts
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WorkOS
The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.
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dlstreamer
This repository is a home to Intel® Deep Learning Streamer (Intel® DL Streamer) Pipeline Framework. Pipeline Framework is a streaming media analytics framework, based on GStreamer* multimedia framework, for creating complex media analytics pipelines.
mediapipe/docs/solutions/pose.md at master · google/mediapipe · GitHub
Project mention: AMD Funded a Drop-In CUDA Implementation Built on ROCm: It's Open-Source | news.ycombinator.com | 2024-02-12ncnn uses Vulkan for GPU acceleration, I've seen it used in a few projects to get AMD hardware support.
https://github.com/Tencent/ncnn
Project mention: AMD MI300X 30% higher performance than Nvidia H100, even with optimized stack | news.ycombinator.com | 2023-12-17> It's not rocket science to implement matrix multiplication in any GPU.
You're right, it's harder. Saying this as someone who's done more work on the former than the latter. (I have, with a team, built a rocket engine. And not your school or backyard project size, but nozzle bigger than your face kind. I've also written CUDA kernels and boy is there a big learning curve to the latter that you gotta fundamentally rethink how you view a problem. It's unquestionable why CUDA devs are paid so much. Really it's only questionable why they aren't paid more)
I know it is easy to think this problem is easy, it really looks that way. But there's an incredible amount of optimization that goes into all of this and that's what's really hard. You aren't going to get away with just N for loops for a tensor rank N. You got to chop the data up, be intelligent about it, manage memory, how you load memory, handle many data types, take into consideration different results for different FMA operations, and a whole lot more. There's a whole lot of non-obvious things that result in high optimization (maybe obvious __after__ the fact, but that's not truthfully "obvious"). The thing is, the space is so well researched and implemented that you can't get away with naive implementations, you have to be on the bleeding edge.
Then you have to do that and make it reasonably usable for the programmer too, abstracting away all of that. Cuda also has a huge head start and momentum is not a force to be reckoned with (pun intended).
Look at TensorRT[0]. The software isn't even complete and it still isn't going to cover all neural networks on all GPUs. I've had stuff work on a V100 and H100 but not an A100, then later get fixed. They even have the "Apple Advantage" in that they have control of the hardware. I'm not certain AMD will have the same advantage. We talk a lot about the difficulties of being first mover, but I think we can also recognize that momentum is an advantage of being first mover. And it isn't one to scoff at.
[0] https://github.com/NVIDIA/TensorRT
Project mention: Distil-Whisper: distilled version of Whisper that is 6 times faster, 49% smaller | news.ycombinator.com | 2023-10-31Just a point of clarification - faster-whisper references it but ctranslate2[0] is what's really doing the magic here.
Ctranslate2 is a sleeper powerhouse project that enables a lot. They should be up front and center and get the credit they deserve.
[0] - https://github.com/OpenNMT/CTranslate2
Project mention: Show HN: I ported Suno AI's Bark model in C for fast realistic audio generation | news.ycombinator.com | 2024-04-24
Project mention: YOLOv7 with TensorRT on Jetson Nano for Object detection | /r/computervision | 2023-05-07Take a look at my tutorial project, it works with models like Yolo and supports dynamic batch sizes. You just need to decode the output: https://github.com/cyrusbehr/tensorrt-cpp-api
NOTE:
The open source projects on this list are ordered by number of github stars.
The number of mentions indicates repo mentiontions in the last 12 Months or
since we started tracking (Dec 2020).
C++ Inference related posts
- Show HN: I ported Suno AI's Bark model in C for fast realistic audio generation
- Bark.cpp: Port of Suno AI's Bark in C/C++ for fast inference
- AMD MI300X 30% higher performance than Nvidia H100, even with optimized stack
- Getting SDXL-turbo running with tensorRT
- QUIK is a method for quantizing LLM post-training weights to 4 bit precision
- Intel OpenVINO 2023.1.0 released
- Intel OpenVINO 2023.1.0 released, open-source toolkit for optimizing and deploying AI inference
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A note from our sponsor - WorkOS
workos.com | 26 Apr 2024
Index
What are some of the best open-source Inference projects in C++? This list will help you:
| Project | Stars | |
|---|---|---|
| 1 | mediapipe | 25,405 |
| 2 | ncnn | 19,176 |
| 3 | TensorRT | 9,065 |
| 4 | jetson-inference | 7,323 |
| 5 | openvino | 5,911 |
| 6 | TNN | 4,281 |
| 7 | lightseq | 3,088 |
| 8 | CTranslate2 | 2,776 |
| 9 | cppflow | 759 |
| 10 | bark.cpp | 513 |
| 11 | dlstreamer | 498 |
| 12 | tensorrt-cpp-api | 462 |
| 13 | EasyOCR-cpp | 26 |
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