Qwen3.5-122B-A10B on DGX Spark: 28.3 → 51 tok/s (+80%)

适用于高性能系统的多进程解压缩软件(A multiprocess decompression software for high-performance system)

🚀 Custom modes for Roo Code VS Code extension - Enhanced AI coding assistance configurations

Dynamic batching library for Deep Learning inference. Tutorials for LLM, GPT scenarios.

A high-performance image processing library designed to optimize and extend the Albumentations library with specialized functions for advanced image transformations. Perfect for developers working in computer vision who require efficient and scalable image augmentation.

This is not a usual PV/UV log analyse tool, but another perspective of web log. It provide fine grained(the minimum is every minute) trouble shooting and performance optimization in a specified time period, based on it's flexible and various summaries.

A Django app that tracks your queries to help optimize them. See Qorme for automated ORM optimization: https://qorme.com?ref=dj-tracker

The repo contains quickstart templates and best practices using Power BI on Databricks SQL, focusing on performance, scalabilty, and operational and cost efficiency

Benchmarks of Spring Boot REST service comparing Java 21 Virtual Threads (Project Loom) with WebFlux (Project Reactor).

A framework for designing, executing and analysing experiment campaigns

🌟 Transform your application with doubao-2api, a seamless bridge to OpenAI's API, enabling easy integration and enhanced functionality.

A batched implementation for efficient Qwen2.5-VL inference.

Autonomous self-learning Agent Plugin for Claude Code 🤖 Automatic learning, real-time dashboard, 40+ linters, OWASP security, CodeRabbit PR reviews. Production-ready with 100% local processing, privacy-first. Free open source AI automation tool

Deep Learning at Scale Training Event at NERSC

High performance async Mssql library for Python.

CUDA matrix multiplication benchmarking on Jetson Orin Nano. Four implementations, three power modes, five matrix sizes. 99.5% mathematical validation. C++/CUDA and Python.

Profine automatically profiles and optimizes PyTorch training jobs on real GPUs, delivering measurable speedups and lower GPU costs before teams waste days tuning configs by hand.

MONTE Carlo Tree Search (MCTS) is a method for finding optimal decisions in a given domain by taking random samples in the decision space and building a search tree accordingly. It has already had a profound impact on Artificial Intelligence (AI) approaches for domains that can be represented as trees of sequential decisions, particularly games …

Makes Intel Arc Pro B70 GPUs actually fast on Ubuntu Server. 11 llama.cpp cherry-picks that fix the big B70 bugs (MoE slot-init SEGV, Q8_0 reorder crash, OOM reorder, missing BF16 GET_ROWS, wrong Xe2 warptile, slow K-quant DMMV, etc.) + Mesa 26 + runtime env workarounds + SYCL/Vulkan backend-selection rules. 2-7x speedup on 4x B70, bench-verified.

DiffPlace: A Conditional Diffusion Framework for Simultaneous VLSI Placement Beyond Sequential Paradigms