TradoxVPS
Ultra fast trading vps | ryzen 9950x vps
What it does
Ultra-fast trading VPS of TradoxVPS. Ryzen 9950x CPU, low latency, 99.999% uptime —ideal for all traders who demand top performance.
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Hi HN, I spent the last few months reading the RISC‑V specification to build the lightest possible sandboxes. The idea behind a vpod is to quickly spin up a Linux sandbox from snapshots (Alpine by default) without any setup or subsystem required. The trade-off for portability and security is raw CPU speed. So we don't expect it to match native workloads with Python or pip, for example. More info is in the README https://github.com/capsulerun/vpod Happy to answer any questions!
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I am sharing a research-grade, open-source trading execution framework that achieves a median end-to-end decision latency of 890 nanoseconds on commodity hardware. The project is designed for education, systems research, and latency instrumentation, not for live trading. It focuses on understanding exactly where every nanosecond goes in a trading execution path. Key features: - Kernel-bypass networking: Direct userspace access to NICs via custom drivers, 20-50 ns RX latency - Lock-free SPSC/MPSC queues: Zero-copy architecture - SIMD feature extraction: About 40 ns per update using…
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I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.
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Hey HN, Henry from Cactus here! We previously released Cactus Needle, a 14MB agentic LLM for tool call, device use, and structured extraction for phones, wearables, smart homes, small robots and microcontrollers. We got really great feedback here, and have now incorporated the suggestions to release Needle 2. The whole model is a single 14MB binary that runs a full session in 28MB of RAM; 45m parameters at 2bit compression. Needle hits 500 tokens/sec decode speed on a Raspberry Pi 5, sits between 400-1,500 tokens/sec on VR devices like Meta Quest 3S and Apple Vision Pro, and ranges…
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