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Showing 7 open source projects for "physical"
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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.
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Cut Data Warehouse Costs by 54%BigQuery delivers 54% lower TCO with exabyte scale and flexible pricing. Free migration tools handle the SQL translation automatically.
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TEACUP
TCP Experiment Automation Controlled Using Python
TEACUP automates many aspects of running TCP performance experiments in a specially-constructed physical testbed. TEACUP enables repeatable testing of different TCP algorithms over a range of emulated network path conditions, bottleneck rate limits and bottleneck queuing disciplines. TEACUP utilises a text-based configuration file to define experiments as combinations of parameters specifying desired network path and end host conditions. -
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This is a sophisticated & integrated simulation and analysis environment for dynamical systems models of physical systems (ODEs, DAEs, maps, and hybrid systems). It supports symbolic math, optimization, continuation, data analysis, biological apps...
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The OpenFire processor is a Xilinx MicroBlaze-compatible processor being modified for use in Cyber Physical Systems research. This material is based upon work supported by the National Science Foundation under Grant No. CPS-0932113.
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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.
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PyPhys is a set of physical quantity classes written in Python. The classes represent physical quantities (like length, pressure, energy, etc.) that can be assigned and extracted in many different units.
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MANIKK is a toolkit for generating numerical interaction parameters -- describing the interaction between metallic atoms in a coherent lattice -- and for performing numerical Monte Carlo-simulations of physical properties of alloy systems.
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FEVal, the Finite Element Evaluator written in Python, provides easy conversion for many Finite Element data formats (both binary and ascii). Mesh modification is very easy. Values of model results can be accessed given coordinates in physical space.
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