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v0.1.3 · Latest tag

Benchmark-Backed Technical Analysis

GPU-accelerated library with 300+ indicators, built for modern quantitative research and production workloads.

300+
Indicators
6.57x
Overall CUDA
97%
Test Coverage

Why VectorAlpha TA Library?

Speed optimized technical analysis indicators

Blazing Fast

Latest 1M x 250 benchmark summaries show 123 indicators faster on CUDA vs Rust, with 12.0x median and 6.57x overall speedup across CUDA-faster indicators.

Comprehensive technical indicator coverage

Complete Coverage

300+ indicators from basic moving averages to advanced patterns, designed for consistent results across research and production.

Extensively tested technical analysis library

Battle Tested

97% test coverage with validation against reference implementations. Used in production by quantitative traders.

Technical Architecture

How It Works

  • CUDA kernels for parallel indicator computation across GPU cores
  • AVX-512 SIMD fallback for CPU execution with vectorized operations
  • Zero-copy memory management with pinned host memory
  • Batch processing engine for multi-symbol analysis

System Requirements

GPU (Optional): NVIDIA GPU with CUDA 13.0+ for maximum performance
CPU Fallback: AVX2 or AVX-512 for vectorized CPU acceleration without GPU
Languages: Rust core library with Python and JavaScript bindings

Performance Benchmarks

Rigorous performance testing against industry standards

Test Environment

Hardware
NVIDIA RTX 4090
24GB VRAM
Ryzen 9 9950X
Dataset
1M OHLCV
5-min bars
~347 days
Method
1000 runs
Median time
Warm cache
Versions
Tulip C (benchmark build)
VA 0.1.3
rustc 1.75
123
CUDA-Faster Indicators
12.0x
Median CUDA Speedup
6.57x
Overall CUDA Speedup

64 indicators are above 10x. Across all CUDA-kernel indicators, overall speedup is 5.16x.

Indicator Performance Comparison

Indicator Rust CPU (ms) CUDA (ms) Speedup
SMA Simple
113.24055 3.51 32.262x
RSI Moderate
122.82 15.07 8.15x
Bollinger Bands Moderate
361.34 3.44 105.06x
MACD Complex
896.67 20.40 43.95x
Stochastic Fast Complex
268.09 5.32 50.44x
ATR Moderate
113.79 21.11 5.39x

* Sample rows from the latest 1M candles x 250 parameter benchmark run on RTX 4090 + Ryzen 9 9950X.

Reproducibility & Fair Comparison

Run These Benchmarks
git clone https://github.com/VectorAlpha-dev/VectorTA
cargo bench --features gpu
View detailed methodology →
Fair Comparison Notes
  • All libraries use single-threaded mode for CPU tests
  • Rust CPU baseline measured in release mode
  • GPU benchmarks include memory transfer overhead
  • Median of 1000 runs to ensure consistency

Built For

HFT & Algo Trading

Real-time indicator computation for sub-second trading decisions

Backtesting Engines

Process years of historical data in seconds for strategy validation

Research & Analytics

Multi-symbol analysis across thousands of assets simultaneously

Quick Start

# Install
cargo add vector-ta
# Use in your code
use vector_ta::{indicators, Config};
let config = Config::gpu();
let sma = indicators::sma(&prices, 20, &config).unwrap();

Key Features

300+ Indicators

Complete set from basic to advanced

Moving averages, oscillators, volatility, volume, momentum, and custom patterns

GPU Acceleration

CUDA kernels with automatic fallback

Automatic device detection with graceful CPU fallback for maximum portability

SIMD Optimized

AVX-512 for maximum CPU performance

Hand-tuned assembly with 256-bit and 512-bit vector instructions

Streaming Support

Real-time data with minimal latency

Process live market data with sub-millisecond indicator updates

Batch Processing

Efficient large dataset handling

Process thousands of symbols in parallel with optimal memory usage

Type Safe

Rust's type system prevents errors

Compile-time guarantees eliminate runtime panics and null pointer errors

Ready to Accelerate Your Analysis?

Use the VectorAlpha TA Library for lightning-fast technical analysis.