#c_lang #accelerator #ack #arq #c #kcp #kcptun #low_latency #protocol #quic #rtc #rtt #socket #srt #tunnel #udp
KCP is a fast and reliable protocol that improves data transmission speed compared to TCP. It reduces average latency by 30-40% and maximum latency by three times, but uses 10-20% more bandwidth. Here’s how it benefits you KCP is designed for speed, making it ideal for real-time applications like online gaming and video streaming.
- **Easy Integration** You can configure various settings such as working mode, window size, and minimum RTO to optimize performance according to your needs.
- **Reliable**: KCP uses selective retransmission and quick retransmit strategies to handle packet loss efficiently, ensuring reliable data transfer.
Overall, KCP offers a simple yet powerful solution to enhance the speed and reliability of your network communications.
https://github.com/skywind3000/kcp
KCP is a fast and reliable protocol that improves data transmission speed compared to TCP. It reduces average latency by 30-40% and maximum latency by three times, but uses 10-20% more bandwidth. Here’s how it benefits you KCP is designed for speed, making it ideal for real-time applications like online gaming and video streaming.
- **Easy Integration** You can configure various settings such as working mode, window size, and minimum RTO to optimize performance according to your needs.
- **Reliable**: KCP uses selective retransmission and quick retransmit strategies to handle packet loss efficiently, ensuring reliable data transfer.
Overall, KCP offers a simple yet powerful solution to enhance the speed and reliability of your network communications.
https://github.com/skywind3000/kcp
GitHub
GitHub - skywind3000/kcp: :zap: KCP - A Fast and Reliable ARQ Protocol
:zap: KCP - A Fast and Reliable ARQ Protocol. Contribute to skywind3000/kcp development by creating an account on GitHub.
#cplusplus #accelerator #llama #llm #low_level_programming #metal #mistral #mixtral #ml #resnet #stable_diffusion #tenstorrent
Tenstorrent's TT-Metal is a powerful tool for developing AI models. It allows users to create custom kernels for their hardware, which can improve performance by reducing memory usage. This is especially useful for large language models (LLMs) like Llama and Mixtral. The TT-Metal system supports efficient data movement and computation, making it beneficial for users who need to run complex AI tasks quickly and effectively. By optimizing how data is stored and processed, TT-Metal helps users achieve better results with less effort.
https://github.com/tenstorrent/tt-metal
Tenstorrent's TT-Metal is a powerful tool for developing AI models. It allows users to create custom kernels for their hardware, which can improve performance by reducing memory usage. This is especially useful for large language models (LLMs) like Llama and Mixtral. The TT-Metal system supports efficient data movement and computation, making it beneficial for users who need to run complex AI tasks quickly and effectively. By optimizing how data is stored and processed, TT-Metal helps users achieve better results with less effort.
https://github.com/tenstorrent/tt-metal
GitHub
GitHub - tenstorrent/tt-metal: :metal: TT-NN operator library, and TT-Metalium low level kernel programming model.
:metal: TT-NN operator library, and TT-Metalium low level kernel programming model. - tenstorrent/tt-metal