Search Results for "parallel-sudoku-solver" - Page 20
Sort By:
Showing 595 open source projects for "parallel-sudoku-solver"
View related business solutions-
$300 Free Credits to Build on Google CloudPut your $300 in credit toward real workloads, then keep building with free monthly usage for 20+ products. No commitment and no charge until you upgrade.
-
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
-
1
Meerkat is a distributed programming environment. It consists of a virtual machine which is suited to parallel processing. The data model is based on the concept of actors, although it is much more permissive than the traditional description.
-
2
Kuhn-Munkres is used inside assignment problem solver application. Instance generator application creates input file for the solver. Checker application verifies the solution computed by the solver. A bash script compiles, executes these apps.
-
3
DKU is an embedded parallel language, or "piggy-back" language that uses function calls to invoke the language's execution model. It tunes task-size to the hardware while hiding hardware details for high performance portability of parallel code.
-
4
Library is a C++ wrapper for libcURL. It adds multi-threading support, jobs based parallel request processing and high level class encapsulation.
-
Go from Code to Production URL in SecondsSkip the Kubernetes configs. Cloud Run handles HTTPS, scaling, and infrastructure automatically. Two million requests free per month.
-
5
This is an Ada implementation of the Dancing Links X Algorithm as in Donald E. Knuth paper. AdaDLX is used to solve the Eight-Queens puzzle, Sudoku grids and Blocs in Box puzzle.
-
6
MicroPather is a path finder and A* solver (astar or a-star) written in platform independent C++ that can be easily integrated into existing code. MicroPather focuses on being a path finding engine for video games but is a generic A* solver.
-
7
LIME (Less-is-More) is parallel/concurrent programming environment based on C. Internally, it uses XML technology to describe tasks and their dependencies. Externally, it offers the ANSI C99 programming as well as a set of visually-oriented interfaces.
-
8
Parallel multithreaded programming language based on ANSI C. Easy to use, comes with a compiler and a runtime system.
-
9
C++ library for calculating the light propagation through large and very small structures (sub wavelength). The used method is the Fourier Modal Method. It can be solve one and two dimensional dielectric structures such as gratings, waveguides etc.
-
Ship Agents FasterGemini Enterprise Agent Platform lets you rapidly build, scale, govern and optimize production-ready agents grounded in your organization's data. The platform enables developers to build custom or pre-built agents for virtually any use case. New customers get $300 in free credits.
-
10
nVidia CUDA and MPI python wrappers. These wrappers are written in pure C no swig or boost necessary. The CUDA wrapper exposes the CUDA runtime and Driver API's.
-
11
Python Integrated Parallel Programming EnviRonment (PIPPER), Python pre-parser that is designed to manage a pipeline, written in Python. It enables automated parallelization of loops. Think of it like OpenMP for Python, but it works in a computer cluster
-
12
This is an implementation of Donald Knuth's Algorithm X ("dancing links"). This is primarily a sudoku generator and solver, though it can be used to solve other exact cover problems.
-
13
42 has six primary goals: foster extreme code reuse; run faster than C; compile to both software and hardware; run faster on reconfigurable computers; support parallel programming; and allow users to extend the language.
-
14
AvatarSAT is a SAT solver that uses machine-learning classifiers to automatically tune the heuristics of an off-the-shelf SAT solver on a per-instance basis.
-
15
The intention of this project is to develop a library and framework which enables Java applications to use multicore processors. Several Ideas to help developers are as follows: Parallel For Work-Stealing Profiler for Parallel Applications ...
-
16
A Java library that provides accelerated downloads of HTTP/HTTPS URIs via the GET and POST methods. Works similar to download managers as requests are made in parallel and chunked for speed.
-
17
-
18
The CodeTime platform covers every aspect of parallel software from authoring, through distribution, to run-time. Its goals are: high programmer productivity; write once, run high performance anywhere; and wide acceptance.
-
19
This is implementation of parallel genetic algorithm with "ring" insular topology. Algorithm provides a dynamic choice of genetic operators in the evolution of. The library supports the 26 genetic operators. This is cross-platform GA written in С++.
-
20
PyGWA is a GPGPU library for Python. It contains Python bindings for AMD CAL and PyGWA.DP - a toy data-parallel programming API.
-
21
The idea is to design simple computers, comparable to vintage homecomputers, large numbers of which are simulated on a PC in parallel. The machines connect to each other, with the goal of seeing efficient structures grow spontaneously, like crystals.
-
22
A GUI comparison tool that automates diffs detection between versions. You can record and play scenarios on two different releases of the same app (in sequential or parallel mode); jDiffChaser compares both screens and shows you the differences.
-
23
Crazy Turtle puzzle game solver utility. Other names: CRAZY TURTLE / LE JEU FOU DE LA TORTUE / NAUGHTY TURTLES / ŠAŠAVE KORNJAČE / NAGAJIVE ŽELVICE / SASAVE KORNJACE
-
24
The PyAALib-JyAALib project is a Python-Java/Jython implementation of the Asynchronous Action Framework based on Pure Object Oriented Concepts. The Massive Parallel Framework in Python Language - Full Compatible with Jython-JAVA
-
25
A data parallel scientific programming model. Compiles efficiently to different platforms like distributed memory (MPI), shared memory multi-processor (pthreads), Cell BE processor, Nvidia Cuda, SIMD vectorization (SSE, Altivec), and sequential C++ code.
