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Top 16 hdf5 Open-Source Projects
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vaex
Out-of-Core hybrid Apache Arrow/NumPy DataFrame for Python, ML, visualization and exploration of big tabular data at a billion rows per second 🚀
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[4] "Is it possible to "flatten" structured data (like JSON?)": https://github.com/saulpw/visidata/discussions/1605
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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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trade-frame
C++ 17 based library (with sample applications) for testing equities, futures, etfs & options based automated trading ideas using DTN IQFeed real time data feed and Interactive Brokers (IB TWS API) for trade execution. Some support for Alpaca & Phemex. Notifications via Telegram [irc: Libra #tradeframe ]
I might be breaking rule #6, but you could take a look at https://github.com/rburkholder/trade-frame, it knows how to deal with options (pricing & greeks), works with chains, can make entrance / exits based upon underlying, knows some combinations, can take profit, handle stops ....
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Project mention: What Every Developer Should Know About GPU Computing | news.ycombinator.com | 2023-10-21
I thought I'd share something with my experience with HPC that applies to many areas, especially in the rise of GPUs.
The main bottleneck isn't compute, it is memory. If you go to talks you're gonna see lots of figures like this one[0] (typically also showing disk speeds, which are crazy small).
Compute is increasing so fast that at this point we finish our operations long faster than it takes to save those simulations or even create the visualizations and put on disk. There's a lot of research going into this, with a lot of things like in situ computing (asynchronous operations, often pushing to a different machine, but needing many things like flash buffers. See ADIOS[1] as an example software).
What I'm getting at here is that we're at a point where we have to think about that IO bottleneck, even for non-high performance systems. I work in ML now, which we typically think of as compute bound, but being in the generative space there are still many things where the IO bottlenecks. This can be loading batches into memory, writing results to disk, or communication between distributed processes. It's one beg reason we typically want to maximize memory usage (large batches).
There's a lot of low hanging fruit in these areas that aren't going to be generally publishable works but are going to have lots of high impact. Just look at things like LLaMA CPP[2], where in the process they've really decreased the compute time and memory load. There's also projects like TinyLLaMa[3] who are exploring training a 1B model and doing so on limited compute, and are getting pretty good results. But I'll tell you from personal experience, small models and limited compute experience doesn't make for good papers (my most cited work did this and has never been published, gotten many rejections for not competing with models 100x it's size, but is also quite popular in the general scientific community who work with limited compute). Wfiw, companies that are working on applications do value these things, but it is also noise in the community that's hard to parse. Idk how we can do better as a community to not get trapped in these hype cycles, because real engineering has a lot of these aspects too, and they should be (but aren't) really good areas for academics to be working in. Scale isn't everything in research, and there's a lot of different problems out there that are extremely important but many are blind to.
And one final comment, there's lots of code that is used over and over that are not remotely optimized and can be >100x faster. Just gotta slow down and write good code. The move fast and break things method is great for getting moving but the debt compounds. It's just debt is less visible, but there's so much money being wasted from writing bad code (and LLMs are only going to amplify this. They were trained on bad code after all)
[0] https://drivenets.com/wp-content/uploads/2023/05/blog-networ...
[1] https://github.com/ornladios/ADIOS2
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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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awips2
Weather forecasting display and analysis package developed by NWS/Raytheon, released as open source software by Unidata.
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h5cpp
C++17 templates between [stl::vector | armadillo | eigen3 | ublas | blitz++] and HDF5 datasets
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ExternData
:page_facing_up: Modelica library for data I/O of CSV, INI, JSON, MATLAB MAT, SSV, TIR, Excel XLS/XLSX and XML files
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matio-cpp
A C++ wrapper of the matio library, with memory ownership handling, to read and write .mat files.
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R-sharp
R# language is a kind of R liked vectorized language implements on .NET environment for the bioinformatics data analysis
Funnily enough already exists, though its not Rust.
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HDF5ImageMarker
Utility to making datasets of images and points coordinates that have been marked up on these images by user
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SaaSHub
SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives
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).
The latest post mention was on 2023-10-21.
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- Option algotrading
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A note from our sponsor - InfluxDB
www.influxdata.com | 18 Apr 2024
Index
What are some of the best open-source hdf5 projects? This list will help you:
| Project | Stars | |
|---|---|---|
| 1 | vaex | 8,171 |
| 2 | visidata | 7,388 |
| 3 | trade-frame | 419 |
| 4 | matio | 323 |
| 5 | hdf5-rust | 293 |
| 6 | gdl | 261 |
| 7 | ADIOS2 | 250 |
| 8 | argos | 171 |
| 9 | awips2 | 164 |
| 10 | h5cpp | 139 |
| 11 | h5pp | 86 |
| 12 | ExternData | 67 |
| 13 | matio-cpp | 53 |
| 14 | H5Record | 45 |
| 15 | R-sharp | 24 |
| 16 | HDF5ImageMarker | 3 |
SaaSHub - Software Alternatives and Reviews
SaaSHub helps you find the best software and product alternatives
www.saashub.com