SiliconMiner

A miner optimized for Apple Silicon M series processors.
Build a miner specifically architected to take full advantage of the M series unified memory shared across the CPU, GPU, and Neural Engine.

Move away from virtualization and code porting of existing projects, and instead build with native libraries and frameworks provided by Apple.

• Accelerate
  https://developer.apple.com/documentation/accelerate

• Core ML
  https://developer.apple.com/documentation/coreml

  • Metal Performance Shaders
    https://developer.apple.com/documentation/metalperformanceshaders
  • Metal Performance Shaders Graph
    https://developer.apple.com/documentation/metalperformanceshadersgraph

• ML Compute
  https://developer.apple.com/documentation/mlcompute

Implementation of the Compute Kernel using the Metal Framework in Swift

To implement the compute kernel for mining XMR using the Metal framework in Swift, follow these steps:

1. Define the Compute Kernel Function: Write Swift code to define the kernel function, its inputs, outputs, and necessary data structures and helper functions.

2. Create a Compute Pipeline State Object: Use the Metal framework to create a compute pipeline state object for the kernel function.

3. Dispatch the Kernel to GPU and Neural Engine Cores: Use the MTLParallelRenderCommandEncoder class to dispatch the kernel to all available cores on the GPU and neural engine.

4. Parallelize the Work on CPU Cores: Use Grand Central Dispatch (GCD) to parallelize the work on the CPU cores.

5. Test and Debug the Code: Run the code and measure its performance. Use debugging tools such as breakpoints and print statements to identify and fix any issues.

6. Refine and Optimize the Code: Experiment with different configurations and fine-tune the code as needed. Optimize the kernel code and parallelization strategies to improve performance.

Integration of RandomX Algorithm

To integrate the RandomX algorithm into the existing code, follow these steps:

1. Add the RandomX Library: Download the RandomX source code from its official repository and include it in your project.

2. Create a Swift Wrapper for RandomX: Create a new Swift file to wrap the RandomX functions and make them accessible from your Swift code.

3. Modify Compute Kernel Functions: Modify the existing compute kernel functions to use the RandomX algorithm for mining.

4. Update the Execute Function: Update the execute function to call the RandomX hash calculation functions.

Building and Running the Project with RandomX Algorithm

To build and run the project with the RandomX algorithm, follow these steps:

1. Clone the Repository: Clone the repository to your local machine.

2. Install Dependencies: Install the necessary dependencies, including the RandomX library.

3. Build the Project: Build the project using Xcode or the Swift Package Manager.

4. Run the Project: Run the project and verify that the RandomX algorithm is being used for mining.