StarRocks, a Linux Foundation project, is a next-generation sub-second MPP OLAP database for full analytics scenarios, including multi-dimensional analytics, real-time analytics, and ad-hoc queries. InfoWorld’s 2023 BOSSIE Award for best open source software.

LakeSoul is an end-to-end, realtime and cloud native Lakehouse framework with fast data ingestion, concurrent update and incremental data analytics on cloud storages for both BI and AI applications.

heavily vectorized c++17 compile time string encryption.

World's fastest log analysis: λ + SQL + JSON + S3

[CVPR 2023] vMAP: Vectorised Object Mapping for Neural Field SLAM

VMAS is a vectorized differentiable simulator designed for efficient Multi-Agent Reinforcement Learning benchmarking. It is comprised of a vectorized 2D physics engine written in PyTorch and a set of challenging multi-robot scenarios. Additional scenarios can be implemented through a simple and modular interface.

Apache Doris Website

vectorized high-level math library

Scalable package delivery logistics simulator built using SingleStore and Vectorized Redpanda

Self-managed thirdparty dependencies for Apache Doris

Backend for columnar, fully orchestrated HEP analyses with pure Python, law and order.

This repo provides a starting point for building applications using SingleStore, Redpanda (by Vectorized), and the Go language. SingleStore is a scale-out relational database built for data-intensive workloads. Redpanda is a Kafka API compatible streaming platform for mission-critical workloads created by the team at Vectorized.

Fast and Strong Burrows Wheeler Model

Plot in NumPy arrays directly, overlay NumPy plots straight over video real-time, plot in Jupyter without a single loop

fast + parallel AlphaZero in PyTorch

TurboMath is an all inline SIMD SSE C++ Math-Library for use in Games and Graphics Windows-Apps

Vectorized Associative Arrays for Python

Vectorized CNN implementation from scratch using only numpy

Sentiment analysis of kinopoisk (https://www.kinopoisk.ru/) reviews. For analysis i used: classification methods (random forest, svc, k-neighbors) neural networks (lstm, mlp).

C++ automatic differentiation library with no dependencies and arbitrary higher order derivatives, stand-alone, header only