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Warp speed Data Transfer (WDT) is an embeddedable library (and command line tool) aiming to transfer data between 2 systems as fast as possible over multiple TCP paths.

C++ cross-platform 3D graphics SDK. Includes demos & helper code (resource loading etc.) to speed up development of Vulkan, OpenGL ES 2.0 & 3.x applications

Unofficial static recompilation of the Xbox 360 version of Need for Speed: Most Wanted (2005): a native port for Steam Deck, Steam Machine, Steam Frame, Linux and Mac (iPhone/iPad: sideload the experimental IPA or build it yourself). Bring your own disc: no game files included. Not affiliated with EA or Valve.

Static recompilation of Need for Speed Underground 2 (SPEED2.EXE x86-32 -> C) with pcrecomp. Bring your own game; no game code or data included.

Can bus monitoring tool based on arduino and can bus shield. Implements CAN ASCII/SLCAN protocol compatible with Lawicel CAN232/CANUSB. Can be used for monitoring low speed CAN (interior can bus of most cars, less than 500kbps). For higher speeds serial port can become a bottleneck in case data density is high.

Unofficial native Android port of Need for Speed: Most Wanted (Xbox Black Edition). The x86 code is statically recompiled to C++ with XboxXBE-Recomp and built for arm64, with a Vulkan renderer, SDL3, touch/controller/keyboard input, and extended graphics options. No emulator, no game assets included.

A drop-in replacement for std::list with 293% faster insertion, 57% faster erasure, 17% faster iteration and 77% faster sorting on average. 20-24% speed increase in use-case testing.

Support vector machines (SVMs) and related kernel-based learning algorithms are a well-known class of machine learning algorithms, for non-parametric classification and regression. liquidSVM is an implementation of SVMs whose key features are: fully integrated hyper-parameter selection, extreme speed on both small and large data sets, full flexibility for experts, and inclusion of a variety of different learning scenarios: multi-class classification, ROC, and Neyman-Pearson learning, and least-squares, quantile, and expectile regression.