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The Synthetic Data Gym (SDGym) is a benchmarking framework for modeling and generating synthetic data. Measure performance and memory usage across different synthetic data modeling techniques – classical statistics, deep learning and more! The SDGym library integrates with the Synthetic Data Vault ecosystem. You can use any of its synthesizers, datasets or metrics for benchmarking. You also customize the process to include your own work. Select any of the publicly available datasets from the...
netstress is a client/server utility designed to stress & benchmark network activity of a given ethernet device or path using simulated (random) real world data and packet sizes instead of fixed data and packet sizes.
These tools, written in J2ME MIDP, run on phones and other small-scale Java devices, to allow software developers understand the particulars of new devices. They quickly uncover aspects such as full class hierarchy, keypad constraints, and general specs.