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dmitrim

dmitrim on Hacker News

Re:Show HN: Graphsignal – ML profiler to speed up training and inference on Tuesday July 05, 2022 @09:31AM (#31987994)
Understand, we'll definitely think about the network part. Just in case it may help, if `nvidia-smi nvlink -gt d` is useful for you in this context then there is a related metric NVLink Throughput Rate to compare runs and monitor. At least you might get an idea whether/how internal links are utilized.
Re:Show HN: Graphsignal – ML profiler to speed up training and inference on Monday July 04, 2022 @06:37PM (#31982439)
For now it only tries to extract NCCL time percentage from the profile, if available, and show it profile summary. Some hints count be in the step trace timeline as well. We are planning to record some NCCL related counters separately as well.

Show HN: Graphsignal – ML profiler to speed up training and inference

Posted by dmitrim on Monday July 04, 2022 @07:40AM
from the show-hn dept.

https://github.com/graphsignal/graphsignal

Hi, Graphsignal founder here. We've launched Graphsignal earlier this year to make machine learning profiling practical and easy to use. Basically, it enables the profile-optimize-benchmark loop. For example, making inference faster by optimizing an ML model, while still maintaining accuracy.We've make a lot of progress that I wanted to share.The profiler now natively supports TensorFlow,...

( Read More... | 7 comments | 16 points | on HN )
Re:Show HN: Graphsignal – Machine learning profiler for training and i... on Tuesday March 15, 2022 @03:29AM (#30682571)
To be more precise, >=2.2 is required for profiler support
Re:Show HN: Graphsignal – Machine learning profiler for training and i... on Sunday March 13, 2022 @01:32PM (#30663615)
Thanks for the feedback, we'll be working on it for sure. At least an explanatory screencast is in the works now, other info material, use cases, etc. are planned.
Re:Show HN: Graphsignal – Machine learning profiler for training and i... on Sunday March 13, 2022 @01:48AM (#30658632)
I'd just use the 2.8, but older 2.x versions should work too. If you encounter are any issues, please let us know via the chat in your account.
Re:Show HN: Graphsignal – Machine learning profiler for training and i... on Friday March 11, 2022 @03:08PM (#30645359)
Many training and inference workloads run in the cloud or on remote servers and profiling them is not straightforward. Having a SaaS makes things much simpler, and also enables additional features, such as team access and sharing. As far as the data privacy is concerned, profiles do not contain any model or raw data, just resource usage, execution statistics, etc., which is acceptable for most of the users to send to a third party. And for the business model, in my opinion, SaaS allows to better monetize the offering and ensure better and up-to-date end product in this case. But this is open, we may consider a free client-side version as well at some point.

Show HN: Graphsignal – Machine learning profiler for training and inference

Posted by dmitrim on Thursday March 10, 2022 @11:18AM
from the show-hn dept.

https://graphsignal.com/

Hi HN, I'm the founder of Graphsignal (https://graphsignal.com). Graphsignal is a machine learning profiler. We've created it to make ML profiling simple and usable. It provides performance summaries, ML operation and kernel level statistics as well as detailed resource usage information necessary for making training and inference faster and more efficient.Profilers help fix performance issues,...

( Read More... | 8 comments | 35 points | on HN )
Re:Show HN: Graphsignal – Operational Machine Learning Model Monitoring on Friday May 07, 2021 @11:53AM (#27077193)
Since ML monitoring is rather a broad term that can be applied to model development, evaluation, retraining and production stages, I'd like to give more context on what Graphsignal is designed for. Our focus is the operational aspects of models deployed to production, e.g. incoming data validity, sudden drift in input and/or output data, etc. making it possible to troubleshoot issues when they detected. So it designed to help MLOps, DevOps and SRE teams to ensure production models' performance and availability.
Re:Practical Go benchmarks on Wednesday March 07, 2018 @09:41AM (#16536656)
Yep, that meant to be capacity, not length. Corrected. Thanks!
Re:Practical Go benchmarks on Wednesday March 07, 2018 @05:45AM (#16535561)
Good point, thanks! The idea behind these benchmarks is to make the results usable in real-world programs, rather than benchmarking real-world programs. I rephrased that sentence to avoid any confusion.
Re:Practical Go benchmarks on Wednesday March 07, 2018 @03:54AM (#16535142)
Thanks for pointing it out. Should clearly not depend on the number of iterations. It's fixed now.
Re:Show HN: StackImpact – Python Production Profiler: CPU, Memory, Exc... on Tuesday June 27, 2017 @04:49PM (#14649290)
We haven't tested it with celery yet. It looks like it should work. gevent is supported by blocking call profiler, and CPU and memory profilers as well as exception and metric reporting are library independent.
Re:Show HN: StackImpact – Python Production Profiler: CPU, Memory, Exc... on Tuesday June 27, 2017 @04:45PM (#14649246)
We haven't tested the whole agent with asyncio applications yet. I guess only CPU profiler was tested during development. We'll do and include it in the docs. For now, if you see any problems, please just open a ticket. Thanks!
Re:Show HN: StackImpact – Python Production Profiler: CPU, Memory, Exc... on Tuesday June 27, 2017 @02:08PM (#14647738)
Yes, the apps were under simulated CPU load, memory allocations, etc. The good thing with sampling profilers is that overhead stays relatively stable even under high load.

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