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neuralmagic
deepsparse
Python2021–2023
neuralmagic / deepsparse · Archived

deepsparse

Sparsity-aware deep learning inference runtime for CPUs

AI & Machine LearningLanguages & CompilersLearning & Reference
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6Distinct people
7Mentions
0Explicit recommenders
3.2KGitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

Sparsity-aware deep learning inference runtime for CPUs

GitHub

Where it is used

No documented product use has been verified yet.

What people are saying

No recommendation phrase was found in the indexed comments.

No classified warning is attached to this page. Read the discussions before treating silence as approval.

Also in these discussions

No other repository is repeatedly linked in the same discussions.

This week on Hacker News

Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 1:49:46 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 month7 dated mentions

Observed mentions: 2021-09-10 18:20:30 UTC to 2023-11-23 08:27:20 UTC.

0123452021-09-01 00:00:00 UTC to 2021-10-01 00:00:00 UTC (exclusive): 5 mentions; 0 submissions, 5 commentsSep 20212021-10-01 00:00:00 UTC to 2021-11-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2021-11-01 00:00:00 UTC to 2021-12-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2021-12-01 00:00:00 UTC to 2022-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2022-01-01 00:00:00 UTC to 2022-02-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2022-02-01 00:00:00 UTC to 2022-03-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2022-03-01 00:00:00 UTC to 2022-04-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2022-04-01 00:00:00 UTC to 2022-05-01 00:00:00 UTC (exclusive): 1 mentions; 1 submissions, 0 comments2022-05-01 00:00:00 UTC to 2022-06-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2022-06-01 00:00:00 UTC to 2022-07-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2022-07-01 00:00:00 UTC to 2022-08-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2022-08-01 00:00:00 UTC to 2022-09-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2022-09-01 00:00:00 UTC to 2022-10-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2022-10-01 00:00:00 UTC to 2022-11-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 commentsOct 20222022-11-01 00:00:00 UTC to 2022-12-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2022-12-01 00:00:00 UTC to 2023-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2023-01-01 00:00:00 UTC to 2023-02-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2023-02-01 00:00:00 UTC to 2023-03-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2023-03-01 00:00:00 UTC to 2023-04-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2023-04-01 00:00:00 UTC to 2023-05-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2023-05-01 00:00:00 UTC to 2023-06-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2023-06-01 00:00:00 UTC to 2023-07-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2023-07-01 00:00:00 UTC to 2023-08-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2023-08-01 00:00:00 UTC to 2023-09-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2023-09-01 00:00:00 UTC to 2023-10-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2023-10-01 00:00:00 UTC to 2023-11-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2023-11-01 00:00:00 UTC to 2023-12-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 commentsNov 2023

Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.

View mention counts and date ranges
UTC ranges include their start and exclude their end. Select a period to filter the source evidence.
PeriodStart (UTC)End (exclusive, UTC)MentionsSubmissionsComments
Sep 20212021-09-01 00:00:00 UTC2021-10-01 00:00:00 UTC505
Oct 20212021-10-01 00:00:00 UTC2021-11-01 00:00:00 UTC000
Nov 20212021-11-01 00:00:00 UTC2021-12-01 00:00:00 UTC000
Dec 20212021-12-01 00:00:00 UTC2022-01-01 00:00:00 UTC000
Jan 20222022-01-01 00:00:00 UTC2022-02-01 00:00:00 UTC000
Feb 20222022-02-01 00:00:00 UTC2022-03-01 00:00:00 UTC000
Mar 20222022-03-01 00:00:00 UTC2022-04-01 00:00:00 UTC000
Apr 20222022-04-01 00:00:00 UTC2022-05-01 00:00:00 UTC110
May 20222022-05-01 00:00:00 UTC2022-06-01 00:00:00 UTC000
Jun 20222022-06-01 00:00:00 UTC2022-07-01 00:00:00 UTC000
Jul 20222022-07-01 00:00:00 UTC2022-08-01 00:00:00 UTC000
Aug 20222022-08-01 00:00:00 UTC2022-09-01 00:00:00 UTC000
Sep 20222022-09-01 00:00:00 UTC2022-10-01 00:00:00 UTC000
Oct 20222022-10-01 00:00:00 UTC2022-11-01 00:00:00 UTC000
Nov 20222022-11-01 00:00:00 UTC2022-12-01 00:00:00 UTC000
Dec 20222022-12-01 00:00:00 UTC2023-01-01 00:00:00 UTC000
Jan 20232023-01-01 00:00:00 UTC2023-02-01 00:00:00 UTC000
Feb 20232023-02-01 00:00:00 UTC2023-03-01 00:00:00 UTC000
Mar 20232023-03-01 00:00:00 UTC2023-04-01 00:00:00 UTC000
Apr 20232023-04-01 00:00:00 UTC2023-05-01 00:00:00 UTC000
May 20232023-05-01 00:00:00 UTC2023-06-01 00:00:00 UTC000
Jun 20232023-06-01 00:00:00 UTC2023-07-01 00:00:00 UTC000
Jul 20232023-07-01 00:00:00 UTC2023-08-01 00:00:00 UTC000
Aug 20232023-08-01 00:00:00 UTC2023-09-01 00:00:00 UTC000
Sep 20232023-09-01 00:00:00 UTC2023-10-01 00:00:00 UTC000
Oct 20232023-10-01 00:00:00 UTC2023-11-01 00:00:00 UTC000
Nov 20232023-11-01 00:00:00 UTC2023-12-01 00:00:00 UTC101

What Hacker News says

7 sources
markurtz·Sep 11, 2021
Disclosure: I work for Neural Magic. Hi deepnotderp, as noted by others the speeds listed here are combining throughput for GPU from Ultralytics to latency for GPU from Neural Magic. We did also include throughput measurements, though, where YOLOv5s was around 3 ms per image on a V100 at fp16 in our testing. All benchmarks were run on AWS instances for repeatability and availability and is likely where the 2 ms vs 3 ms discrepancy comes from (slower memory transfer on the AWS machine vs the one Ultralytics used). Note, though, a slower overall machine will also affect CPU results as well. We benchmarked using the available PyTorch APIs mimicking what was done for Ultralytics benchmarking. This code is open sourced for viewing and use here: https://github.com/neuralmagic/deepsparse/blob/main/examples...
In YOLOv5 on CPUs: Sparsifying to Achieve GPU-Level Performance

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