purem 2.1.0

High-performance mapping function for mixed-type arrays

Overview

Purem is an advanced high-performance computational library optimized for vectorized mathematical operations. This project focuses on efficient execution of element-wise transformations, including softmax, exp, and other mathematical functions, leveraging highly optimized assembly code for modern architectures.

Key Features

Purem is a blazing-fast AI math engine that turns your Python formulas into native-speed vectorized execution. Achieve up to 80× faster performance on CPU/GPU/TPU — no rewrites, no dependencies, just speed. Designed for ML researchers, scientific computing, and production-grade workloads that can’t afford to wait.

—

🔧 Installation

Install the Python wrapper via pip:

pip install purem

📦 Note: Installation is quick, but purem must be initialized with a license before use. Setup takes less than a minute – we’re ready when you are: https://worktif.com/#start

—

🚀 Quickstart

1. Import and Initialize:

   from purem import purem
   
   purem.configure(license_key='your-license-key')  # Auto-downloads and configures backend

Alternatively, if you already have the backend .so file:

from purem import purem

purem.softmax([...])  # Initialized from local ./lib/libpurem.so

—

📁 Local Library Structure

If the backend .so is already downloaded manually, place it here:

your_project/
├── main.py
├── lib/
│   └── libpurem.so

—

🔐 License-Based Activation

To automatically download and configure the backend library:

1. Call purem.configure(license_key='<your-license-key>')

2. The system will download the .so file to ./lib/

3. All functions will become available instantly after initialization

Without a valid license key:

• No .so will be downloaded

• The library won’t work unless you provide the .so manually

—

🧠 Available Functions

After initialization, you can call:

from purem import purem

purem.softmax([...])
...

Full function list: https://worktif.com/docs/basic-usage

—

📦 Packaging Notes

This package does not bundle the .so file. You are required to:

• Use a license key to download it dynamically

• Alternatively, place it manually into ./lib/ folder before calling init()

—

🧪 Benchmark Tutorial

Visit the Benchmark Tutorial: https://worktif.com/#benchmarks

• How Purem compares to NumPy, PyTorch and Numba

• How it reaches low-level performance via native execution

• Why it’s faster than traditional Python-based computation

—

📧 Distribution and Licensing

We do not provide direct download links for the backend. All users must either:

• Use their license key to install

• Or receive .so file from verified sources

For access, contact us or visit: https://worktif.com/documents/terms-of-service

—

📚 Full Example

import numpy as np
from purem import purem

# Automatic setup using license key
try:
    purem.configure(license_key='<your-license-key>')
except Exception as e:
    print(f"Setup failed: {e}")

data = np.array([1.0, 2.0, 3.0], dtype=float)
output = purem.softmax(data)

print(output)

—

🧠 Why Purem?

• 🔥 High level performance with zero Python overhead

• 🧪 Built-in benchmarking and scientific accuracy

• 🧩 Easy plug-and-play design

• 🔐 Secure and license-aware system

—

🛠 Advanced Usage & API Docs

Coming soon…