KHkhelwegen·Mar 5, 2020Submission
Show HN: Larq Compute Engine – Efficient Deployment of Binarized Neural Networks
2 points · Open discussionlarq
compute-engine
C++2020–2020
larq / compute-engine
compute-engine
Highly optimized inference engine for Binarized Neural Networks
2Distinct people
4Mentions
0Explicit recommenders
258GitHub stars
What to know before exploring
What it is
Highly optimized inference engine for Binarized Neural Networks
GitHub
Where it is used
No documented product use has been verified yet.
What people are saying
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Also in these discussions
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This week on Hacker News
Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 12:54:37 PM UTC.
No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.
Mentions over time
HN mentions by day4 dated mentions
Observed mentions: 2020-02-17 17:29:16 UTC to 2020-03-05 13:30:53 UTC.
Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.
View mention counts and date ranges
| Period | Start (UTC) | End (exclusive, UTC) | Mentions | Submissions | Comments |
|---|---|---|---|---|---|
| Feb 17 | 2020-02-17 00:00:00 UTC | 2020-02-18 00:00:00 UTC | 2 | 1 | 1 |
| Feb 18 | 2020-02-18 00:00:00 UTC | 2020-02-19 00:00:00 UTC | 0 | 0 | 0 |
| Feb 19 | 2020-02-19 00:00:00 UTC | 2020-02-20 00:00:00 UTC | 1 | 1 | 0 |
| Feb 20 | 2020-02-20 00:00:00 UTC | 2020-02-21 00:00:00 UTC | 0 | 0 | 0 |
| Feb 21 | 2020-02-21 00:00:00 UTC | 2020-02-22 00:00:00 UTC | 0 | 0 | 0 |
| Feb 22 | 2020-02-22 00:00:00 UTC | 2020-02-23 00:00:00 UTC | 0 | 0 | 0 |
| Feb 23 | 2020-02-23 00:00:00 UTC | 2020-02-24 00:00:00 UTC | 0 | 0 | 0 |
| Feb 24 | 2020-02-24 00:00:00 UTC | 2020-02-25 00:00:00 UTC | 0 | 0 | 0 |
| Feb 25 | 2020-02-25 00:00:00 UTC | 2020-02-26 00:00:00 UTC | 0 | 0 | 0 |
| Feb 26 | 2020-02-26 00:00:00 UTC | 2020-02-27 00:00:00 UTC | 0 | 0 | 0 |
| Feb 27 | 2020-02-27 00:00:00 UTC | 2020-02-28 00:00:00 UTC | 0 | 0 | 0 |
| Feb 28 | 2020-02-28 00:00:00 UTC | 2020-02-29 00:00:00 UTC | 0 | 0 | 0 |
| Feb 29 | 2020-02-29 00:00:00 UTC | 2020-03-01 00:00:00 UTC | 0 | 0 | 0 |
| Mar 1 | 2020-03-01 00:00:00 UTC | 2020-03-02 00:00:00 UTC | 0 | 0 | 0 |
| Mar 2 | 2020-03-02 00:00:00 UTC | 2020-03-03 00:00:00 UTC | 0 | 0 | 0 |
| Mar 3 | 2020-03-03 00:00:00 UTC | 2020-03-04 00:00:00 UTC | 0 | 0 | 0 |
| Mar 4 | 2020-03-04 00:00:00 UTC | 2020-03-05 00:00:00 UTC | 0 | 0 | 0 |
| Mar 5 | 2020-03-05 00:00:00 UTC | 2020-03-06 00:00:00 UTC | 1 | 1 | 0 |
What Hacker News says
4 sourcesShow HN: Larq – Binarized Neural Network Inference with MLIR and TFLite
4 points · Open discussionAuthor here: I work at Plumerai, a startup that’s building chips for efficient inference of binarized neural network (BNN). We previously open-sourced Larq [1], the library we use to build and train BNNs, and Larq Zoo [2], our repository of pre-trained BNNs from the literature. Now we’re opening up the deployment side as well with Larq Compute Engine (LCE).
You can grab a BNN from Larq Zoo (or build and train your own using Larq), use the MLIR converter in LCE to convert it into a TensorFlow Lite-compatible Flatbuffer file, and then use the LCE runtime to run inference on mobile and edge devices like Android phones [3] and the Raspberry Pi [4] (support for Armv8-M microcontrollers coming soon).
Internally at Plumerai, LCE has enabled our ML researchers to benchmark different BNN architectures and downstream application implementations on
Read the rest
real hardware, so we’re excited to see what other developers and researchers will use it for!
Happy to answer any questions :)
[1] docs: https://docs.larq.dev, github: https://github.com/larq/larq
[2] docs: https://docs.larq.dev/zoo, github: https://github.com/larq/zoo
[3] docs: https://github.com/larq/compute-engine/blob/master/docs/quic...
[4] docs: https://github.com/larq/compute-engine/blob/master/docs/buil...
Show HN: Larq – Binarized Neural Network Inference with MLIR and TFLite
6 points · Open discussion