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Source channel @githubtrending · Post #15571 · Mar 18

#python#newton_physics#nvidia_warp#physics_simulation#robotics Newton is a free, open-source GPU-accelerated physics engine for fast, accurate robot simulations, built by NVIDIA, Google DeepMind, and Disney Research. Install easily with `pip install "newton[examples]"` and run demos like pendulums, humanoids, cloth, cables, or hands via simple Python commands—it supports Linux/Windows/macOS with NVIDIA GPUs. You benefit by quickly testing robotics ideas with high-speed, differentiable physics for AI training, real-time adaptability, and complex tasks like manipulation, cutting weeks off development time. https://github.com/newton-physics/newton

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@githubtrending · Post #14772 · 06/01/2025, 12:00 AM

#cplusplus#cache#cpp#database#fibers#in_memory#in_memory_database#key_value#keydb#memcached#message_broker#multi_threading#nosql#redis#valkey#vector_search Dragonfly is a modern in-memory data store compatible with Redis and Memcached, offering up to 25 times higher throughput and better cache efficiency while using up to 80% fewer resources. It scales well with larger servers, supports many Redis commands, and features a unique, memory-efficient cache and fast snapshotting. Dragonfly provides low latency, high performance, and is easy to configure with familiar Redis options. Its design ensures atomic operations and efficient resource use, making it ideal for fast, cost-effective cloud applications needing real-time data access and high scalability. This means you get faster, more efficient caching and data handling with minimal changes to your existing setup[5][2][4]. https://github.com/dragonflydb/dragonfly