Open source machine learning inference accelerators on FPGA
Tom from Tensil here - happy to answer questions! We developed Tensil to bring custom ML accelerators to people who don't have the resources of companies like Google, Facebook and Tesla. Currently, we're focused on supporting convolutional neural network inference on edge FPGA (field programmable gate array) platforms, but we aim to support all model architectures on a wide variety of fabrics for both training and inference. Tensil is different from other ML accelerators in that it is open source and really easy to use. For example, you can generate a custom accelerator with one command: $…
Open source machine learning inference accelerators on FPGA launched on March 9, 2022 with 57 votes, #946 of 3,153 launches that month and more than 90% of that year's launches. The site was still online in September 2026, 4 years on.
In plain words
Tensil is an open-source platform for creating custom machine learning inference accelerators on FPGAs. It enables developers without large resources to build and deploy convolutional neural networks on edge devices through simple command-line tools. The platform streamlines the process from accelerator generation to model compilation to inference execution, aiming to eventually support all model architectures across various hardware types for both training and inference workloads.
written from the facts on this page · September 2026
From the sources
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In the maker’s words, at launch
Tom from Tensil here - happy to answer questions! We developed Tensil to bring custom ML accelerators to people who don't have the resources of companies like Google, Facebook and Tesla. Currently, we're focused on supporting convolutional neural network inference on edge FPGA (field programmable gate array)…
Does a similar job
all alternatives →- IBI built a toy TPU that can do inference and training on the XOR problem2025 · tinytpu.com · ▲134
We wanted to do something very challenging to prove to ourselves that we can do anything we put our mind to. The reasoning for why we chose to build a toy TPU specifically is fairly simple: - Building a chip for ML workloads seemed cool - There was no well-documented open source repo for an ML accelerator that performed both inference and training None of us have real professional experience in hardware design, which, in a way, made the TPU even more appealing since we weren't able to estimate exactly how difficult it would be. As we worked on the initial stages of this project, we…
Pip install inference, open source computer vision deployment2023 · github.com · ▲71Deploying vision models is time consuming and tedious. Setting up dependencies. Fixing conflicts. Configuring TRT acceleration. Flashing (and re-flashing) NVIDIA Jetsons. A streamlined, developer-friendly solution for inference is needed. We, the Roboflow team, have been hard at work open sourcing Inference, an open source vision deployment solution. Our solution is designed with developers in mind, offering a HTTP-based interface. Run models on your hardware without having to write architecture-specific inference code. Here's a demo showing how to go from a model to GPU inference on a video…
TensorZero2025 · github.com · ▲307Hi HN! We're Gabriel & Viraj, and we're excited to open source TensorZero. To be a little cheeky, TensorZero is an open-source platform that helps LLM applications graduate from API wrappers into defensible AI products. 1. Integrate our model gateway 2. Send metrics or feedback 3. Unlock compounding improvements in quality, cost, and latency It enables a data & learning flywheel for LLMs by unifying: • Inference: one API for all LLMs, with <1ms P99 overhead • Observability: inference & feedback → your database • Optimization: better prompts, models, inference strategies • Experimentation:…
Tensorflow Research Cloud2017 · sites.research.google · ▲288Accelerating open machine learning research with Cloud TPUs
Tiny-vLLM – high performance LLM inference engine in C++ and CUDAMay 2026 · github.com · ▲205Build your own high performance LLM inference engine in C++ and CUDA - a smaller version of vLLM - jmaczan/tiny-vllm
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