Developer Hub

Build FPGA-accelerated models for oncology research. This platform leverages the PYNQ Z1 FPGA to achieve 100-1000x speedups for computationally intensive simulations.

PYNQ Z1

Target Hardware

100-1000x

Typical Speedup

Job Types Supported

Python

Primary SDK

Quick Start Guide

Follow these steps to create your first FPGA-accelerated model

Set Up Development Environment

30 min

Install Vivado, PYNQ SDK, and configure your workspace

Understand the Architecture

1 hour

Learn about PYNQ Z1 hardware and overlay structure

Create Your First IP Block

2 hours

Build a simple accelerator using Vivado HLS

Integrate with OncologyAI

1 hour

Connect your model to the platform's job queue

Essential

FPGA Model Tutorial

Complete guide to building FPGA-accelerated oncology models

Reference

API Reference

REST API documentation for job submission and results

Samples

Example Models

Sample implementations for drug screening and tumor growth

Command Palette

Developer Hub

Set Up Development Environment

Understand the Architecture

Create Your First IP Block

Integrate with OncologyAI