BLIS.jl
rr
BLIS.jl | rr | |
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1 | 102 | |
26 | 8,665 | |
- | 1.1% | |
1.3 | 9.6 | |
about 1 year ago | 4 days ago | |
Julia | C++ | |
BSD 3-clause "New" or "Revised" License | GNU General Public License v3.0 or later |
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BLIS.jl
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Why Fortran is easy to learn
It doesn't look like you're measuring factorization performance? OpenBLAS matrix-matrix multiplication is fine, it just falls apart when going to things like Cholesky and LU.
> not the default, I've now checked
Whatever the Julia default build is doing, so probably not the recursive LAPACK routines then if that's how it's being built. If there's a better default that's worth an issue.
> That said, I don't understand why people avoid AMD's BLAS/LAPACK
There just isn't a BLIS wrapper into Julia right now, and it's much easier to just write new BLAS tools than to build wrappers IMO. It makes it very easy to customize to nonstandard Julia number types too. But I do think that BLIS is a great project and I would like to see it replace OpenBLAS as the default. There's been some discussion to make it as easy as MKL (https://github.com/JuliaLinearAlgebra/BLIS.jl/issues/3).
rr
- rr: Lightweight Recording and Deterministic Debugging
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Hermit is a hermetic and reproducible sandbox for running programs
I think this tool must share a lot techniques and use cases with rr. I wonder how it compares in various aspects.
https://rr-project.org/
rr "sells" as a "reversible debugger", but it obviously needs the determinism for its record and replay to work, and AFAIK it employs similar techniques regarding system call interception and serializing on a single CPU. The reversible debugger aspect is built on periodic snapshotting on top of it and replaying from those snapshots, AFAIK. They package it in a gdb compatible interface.
Hermit also lists record/replay as a motivation, although it doesn't list reversible debugging in general.
- Rr: Lightweight Recording and Deterministic Debugging
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Deep Bug
Interesting. Perhaps you can inspect the disassembly of the function in question when using Graal and HotSpot. It is likely related to that.
Another debugging technique we use for heisenbugs is to see if `rr` [1] can reproduce it. If it can then that's great as it allows you to go back in time to debug what may have caused the bug. But `rr` is often not great for concurrency bugs since it emulates a single-core machine. Though debugging a VM is generally a nightmare. What we desperately need is a debugger that can debug both the VM and the language running on top of it. Usually it's one or the other.
> In general I’d argue you haven’t fixed a bug unless you understand why it happened and why your fix worked, which makes this frustrating, since every indication is that the bug exists within proprietary code that is out of my reach.
Were you using Oracle GraalVM? GraalVM community edition is open source, so maybe it's worth checking if it is reproducible in that.
[1]: https://github.com/rr-debugger/rr
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So you think you want to write a deterministic hypervisor?
https://rr-project.org/ had the same problem. They use the retired conditional branch counter instead of instruction counter, and then instruction steeping until at the correct address.
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Is Something Bugging You?
That'll work great for your Distributed QSort Incorporated startup, where the only product is a sorting algorithm.
Formal software verification is very useful. But what can be usefully formalized is rather limited, and what can be formalized correctly in practice is even more limited. That means you need to restrict your scope to something sane and useful. As a result, in the real world running thousands of tests is practically useful. (Well, it depends on what those tests are; it's easy to write 1000s of tests that either test the same thing, or only test the things that will pass and not the things that would fail.) They are especially useful if running in a mode where the unexpected happens often, as it sounds like this system can do. (It's reminiscent of rr's chaos mode -- https://rr-project.org/ linking to https://robert.ocallahan.org/2016/02/introducing-rr-chaos-mo... )
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When "letting it crash" is not enough
The approach of check-pointing computation such that it is resumable and restartable sounds similar to a time-traveling debugger, like rr or WinDbg:
https://rr-project.org/
https://learn.microsoft.com/windows-hardware/drivers/debugge...
- When I got started I debugged using printf() today I debug with print()
- Rr: Record and Replay Debugger – Reverse Debugger
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OpenBSD KDE Plasma Desktop
https://github.com/rr-debugger/rr?tab=readme-ov-file#system-...
What are some alternatives?
SuiteSparse.jl - Development of SuiteSparse.jl, which ships as part of the Julia standard library.
CodeLLDB - A native debugger extension for VSCode based on LLDB
18337 - 18.337 - Parallel Computing and Scientific Machine Learning
rrweb - record and replay the web
GPUCompiler.jl - Reusable compiler infrastructure for Julia GPU backends.
gef - GEF (GDB Enhanced Features) - a modern experience for GDB with advanced debugging capabilities for exploit devs & reverse engineers on Linux
MPI.jl - MPI wrappers for Julia
Module Linker - browse modules by clicking directly on "import" statements on GitHub
quickjs - Public repository of the QuickJS Javascript Engine.
nbdev - Create delightful software with Jupyter Notebooks
TriangularSolve.jl - rdiv!(::AbstractMatrix, ::UpperTriangular) and ldiv!(::LowerTriangular, ::AbstractMatrix)
clog-cli - Generate beautiful changelogs from your Git commit history