golomb-solver
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golomb-solver
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Ask HN: Do you use an optimization solver? Which one? Why? Do you like it?
CPLEX (by IBM). The documentation can be a bit thin sometimes. But its fast. Most benchmarks place it ahead of the google cloud products.
For fun I made this Golomb ruler solver using cplex: https://github.com/strateos/golomb-solver
exact
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New release
Version 1.0.0 of Exact is released.
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Ask HN: Where to run embarrassingly parallel, Integer, no SIMD workloads?
>> The workload is memory bound not compute bound.
> I don't think so? How many gigabytes per second per core are you processing?
That's what the Intel VTune profiler tells me. 39.2% Memory bound = 21,7% of clock ticks L1 bound (execution stalled for data that was in L1) + 12.4% L3 bound on a Haswell 4 core Xeon.
> If for some reason you can talk about this problem to random SIMD programmers online privately but you cannot post about this problem publicly
I can talk about it publicly. I just did not want to distracted from the actual hardware question. I recently started to contribute to this https://gitlab.com/JoD/exact open source project. The algorithm tries to find a valid assignment for a bunch of equations of this form 4x1 -3x57 +1* not(x1232) <= 4 (there are special cases already accelerated). We guess an assignment for a certain variable, check all constraints, sometimes constraints imply other assignments to other variables (if x1 is true and x1232 is false x57 has to be true) then those get propagated to. One technique is called watch propagation and can be done for the SAT family of clauses. This technique is in incompatible with branching along assignments. I find SIMD over clauses dubious, as they are mostly random accessed of different length and sparse. The embarrassing parallelization comes from being able to work one different parts of the parameter space and exchange clauses learned from conflicts. We are currently not doing that yet but plan to do something HordeSAT like over MPI (there is different slightly cleverer tree exchange variant over MPI all to all but i do not have that reference handy).
We have some horrible sins (such a virtual method table look ups in loops, no -march=native compiler flags in main branch, ...) which the main developer created and we have not cleaned up. If i could nerd snipe you to run some experiments with that codebase and contribute some SIMD loops (with -march=native -mtune=native only 4 functions are currently SIMD, none are significant to the performance) that be great. For all the divisibilty checking i currently plan this: https://www.reddit.com/r/exact/comments/wokfhl/resource_on_f... (we spend 3% of compute time in the standard libraries modulo)
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Ask HN: Do you use an optimization solver? Which one? Why? Do you like it?
I use JuMP as modeling language. For MILP i am usually using Gurobi or SCIP. For ILP problems have have been looking in to the exact solver https://gitlab.com/JoD/exact which seems quiet promising.
For NLP i usually go with either https://worhp.de/ or just IpOpt.
What are some alternatives?
HiGHS - Linear optimization software
osqp - The Operator Splitting QP Solver
python-mip - Python-MIP: collection of Python tools for the modeling and solution of Mixed-Integer Linear programs
optaplanner-quickstarts - Mirror of https://github.com/apache/incubator-kie-optaplanner-quickstarts
csips - A pure-python integer programming solver
clpz - Constraint Logic Programming over Integers
or-tools - Google's Operations Research tools: