This article explores the challenges and possibilities of writing portable and efficient SIMD code in Rust, aiming for a "fearless SIMD" approach with high-level, safe, and composable primitives.
This article details the process of building a fast vector search system for a large legal dataset (Australian High Court decisions). It covers choosing embedding providers, performance benchmarks, using USearch and Isaacus embeddings, and the importance of API terms of service. It focuses on achieving speed and scalability while maintaining reasonable accuracy.
This tutorial compares Polars and pandas, covering syntax, performance, LazyFrames, conversions, and plotting to help you choose the right library for your data analysis needs.
A detailed guide for running the new gpt-oss models locally with the best performance using `llama.cpp`. The guide covers a wide range of hardware configurations and provides CLI argument explanations and benchmarks for Apple Silicon devices.
The fast, feature-rich, GPU based terminal emulator. It's capable, scriptable, composable, cross-platform, and innovative.
Pogocache is a new open-source caching software focusing on low latency and CPU efficiency. It supports multiple protocols (Memcache, Valkey/Redis, HTTP, PostgreSQL) and claims better throughput and lower latency than alternatives. It's written in C and designed for high performance and scalability.
timep is an efficient and accurate state-of-the-art trap-based profiler and flamegraph generator for bash code. It maps the full call-stack tree for the bash code being profiled, and (optionally) uses that call-stack tree to generate a FlameGraph of the profiled bash commands!
The article details the author's investigation into slow Python tool startup times. They used the `python -X importtime` feature to identify import bottlenecks and visualized the resulting data using Kevin Michel's `python-importtime-graph` tool, revealing a dense treemap of import times.
Pandas 3.0 will significantly boost performance by replacing NumPy with PyArrow as its default engine, enabling faster loading and reading of columnar data.
LocalScore is an open benchmark to evaluate local AI task performance across various hardware configurations, measuring Prompt Processing speed, Token Generation speed, Time-to-First-Token (TTFT), and a combined LocalScore.
