path: root/src/main.rs

use std::env::{self, Args};
use std::mem;
use std::num::NonZeroU64;
use std::ops::RangeBounds;
use std::time::Instant;

use wgpu::{BufferUsages, SubmissionIndex, include_wgsl};
use wgpu::util::DeviceExt;
use wgpu::wgc::command;



const PALETTE: &[u8] = include_bytes!("../palette.txt"); 
const PALETTE_SIZE: usize =  PALETTE.len();

const BATCH_SIZE : u64 = (1 << 16) - 64; 
const MAX_ITER : u64 = 1 << 32;
// const BATCH_SIZE : u64 = 8; 
// const MAX_ITER : u64 = 2; 

const INPUT_SIZE:u64 =  512 / 8 * 8;
const INSIZE_SIZE:u64= 32 / 8; 
const OUTPUT_SIZE:u64= 256 / 8; 
const INPUT_BUF_SIZE :u64= INPUT_SIZE * BATCH_SIZE; 
const SIZES_BUF_SIZE :u64= INSIZE_SIZE * BATCH_SIZE;
const OUTPUT_BUF_SIZE:u64= OUTPUT_SIZE * BATCH_SIZE;  

fn get_arg(args: &mut Args, pname: &String , name: &'static str) -> String {
    args.next().unwrap_or_else(|| panic!("Argument missing: {}\nUsage: {} value prev bits", name, pname)).clone()
}


struct NonceIter {
    digits: Vec<usize>, 
}

impl NonceIter {
    fn new_with_capacity(capacity: usize) -> Self {
        Self {
            digits: Vec::with_capacity(capacity)    
        }
    }
} 

impl Iterator for NonceIter {
    type Item = NonceElement;
    fn next(&mut self) -> Option<Self::Item> {
        let mut carry = 1; 
        let mut cursor = 0; 
        while carry > 0 { 
           if let Some(d) = self.digits.get_mut(cursor)  {
                if *d + carry >= PALETTE_SIZE {
                   *d = (*d + carry) % PALETTE_SIZE; 
                } else {
                   *d += carry; 
                   carry = 0; 
                }
           } else {
                self.digits.push(carry);
                carry = 0; 
           } 
           cursor += 1;
        }
        Some(NonceElement::from_digits(&self.digits))
    }

}

#[derive(Debug)]
struct NonceElement {
    pub bytes: Vec<u8>
}

impl NonceElement {
    fn from_digits(digits: &Vec<usize>) -> Self {
        let mut bytes = Vec::with_capacity(digits.len());
        for d in digits {
           bytes.push(PALETTE[*d]) 
        } 
        Self {
            bytes
        }
    }
    fn to_hash_input(&self, value: &String, prev: &String) -> String {
        let mut out = String::with_capacity(self.bytes.len() + value.len() + prev.len()); 
        out += value; 
        out += prev; 
        out += str::from_utf8(self.bytes.as_slice()).expect("Invalid bytes in pallette");
        out 
    }
}


/// Swap chain. We Have Swap Chains At Home Edition. 
/// When given an index, returns the first tuple entry if the index is even, and the second if it's
/// odd. 
fn swaptuple_get<T>(tup :&(T,T), i: u64) -> &T {
    if i.is_multiple_of(2){ &tup.0 } else { &tup.1 }  
} 
/// Swap chain. We Have Swap Chains At Home Edition. Mutable Edition.  
/// When given an index, returns the first tuple entry if the index is even, and the second if it's
/// odd, but now mutable. 
fn swaptuple_get_mut<T>(tup :& mut (T,T), i: u64) -> & mut T {
    if i.is_multiple_of(2) { &mut tup.0 } else { &mut tup.1 }  
} 

fn main() {
    let mut args = env::args(); 

    let pname: String = args.next().expect("Program name should always be included.");
    let value: String = get_arg(&mut args, &pname, "value");
    let prev: String = get_arg(&mut args, &pname, "prev");
    let bits: u16 = get_arg(&mut args, &pname, "bits").parse().unwrap();

    // We first initialize an wgpu `Instance`, which contains any "global" state wgpu needs.
    //
    // This is what loads the vulkan/dx12/metal/opengl libraries.
    env_logger::init();

    let instance = wgpu::Instance::new(&wgpu::InstanceDescriptor::from_env_or_default());
    let areq = wgpu::RequestAdapterOptions {power_preference: wgpu::PowerPreference::HighPerformance, ..Default::default()};
    let adapter =
        pollster::block_on(instance.request_adapter(&areq))
            .expect("Failed to create adapter");

    // Print out some basic information about the adapter.
    println!("Running on Adapter: {:#?}", adapter.get_info());

    // Check to see if the adapter supports compute shaders. While WebGPU guarantees support for
    // compute shaders, wgpu supports a wider range of devices through the use of "downlevel" devices.
    let downlevel_capabilities = adapter.get_downlevel_capabilities();
    if !downlevel_capabilities
        .flags
        .contains(wgpu::DownlevelFlags::COMPUTE_SHADERS)
    {
        panic!("Adapter does not support compute shaders");
    }

    // We then create a `Device` and a `Queue` from the `Adapter`.
    //
    // The `Device` is used to create and manage GPU resources.
    // The `Queue` is a queue used to submit work for the GPU to process.
    let (device, queue) = pollster::block_on(adapter.request_device(&wgpu::DeviceDescriptor {
        label: None,
        required_features: wgpu::Features::empty(),
        required_limits: wgpu::Limits::downlevel_defaults(),
        experimental_features: wgpu::ExperimentalFeatures::disabled(),
        memory_hints: wgpu::MemoryHints::MemoryUsage,
        trace: wgpu::Trace::Off,
    }))
    .expect("Failed to create device");

    // Create a shader module from our shader code. This will parse and validate the shader.
    //
    // `include_wgsl` is a macro provided by wgpu like `include_str` which constructs a ShaderModuleDescriptor.
    // If you want to load shaders differently, you can construct the ShaderModuleDescriptor manually.
    let module = device.create_shader_module(wgpu::include_wgsl!("shader_own.wgsl"));
    
    let mut iter = NonceIter::new_with_capacity((512 - prev.len() - value.len()));

    // Create a buffer with the data we want to process on the GPU.
    //
    // `create_buffer_init` is a utility provided by `wgpu::util::DeviceExt` which simplifies creating
    // a buffer with some initial data.
    //
    // We use the `bytemuck` crate to cast the slice of f32 to a &[u8] to be uploaded to the GPU.
    let input_data_buffer = device.create_buffer(&wgpu::BufferDescriptor {
        label: Some("Input"),
        size:  INPUT_BUF_SIZE,
        usage: wgpu::BufferUsages::union(BufferUsages::STORAGE, BufferUsages::COPY_DST),
        mapped_at_creation: false,
    });
    
    let data_size_buffer = device.create_buffer(&wgpu::BufferDescriptor {
        label: Some("Data Size"),
        size:  SIZES_BUF_SIZE,
        usage: wgpu::BufferUsages::union(BufferUsages::STORAGE, BufferUsages::COPY_DST),
        mapped_at_creation: false,
    });

    // Now we create a buffer to store the output data.
    let output_data_buffer = device.create_buffer(&wgpu::BufferDescriptor {
        label: Some("Output"),
        size: OUTPUT_BUF_SIZE,
        usage: wgpu::BufferUsages::STORAGE | wgpu::BufferUsages::COPY_SRC,
        mapped_at_creation: false,
    });

    // Finally we create a buffer which can be read by the CPU. This buffer is how we will read
    // the data. We need to use a separate buffer because we need to have a usage of `MAP_READ`,
    // and that usage can only be used with `COPY_DST`.
    let download_buffer_0 = device.create_buffer(&wgpu::BufferDescriptor {
        label: Some("Download_0"),
        size: OUTPUT_BUF_SIZE,
        usage: wgpu::BufferUsages::COPY_DST | wgpu::BufferUsages::MAP_READ,
        mapped_at_creation: false,
    });

    // We use a second buffer to flip stuff
    let download_buffer_1 = device.create_buffer(&wgpu::BufferDescriptor {
        label: Some("Download_1"),
        size: OUTPUT_BUF_SIZE,
        usage: wgpu::BufferUsages::COPY_DST | wgpu::BufferUsages::MAP_READ,
        mapped_at_creation: false,
    });

    let dl_bufs = (download_buffer_0, download_buffer_1); 

    // A bind group layout describes the types of resources that a bind group can contain. Think
    // of this like a C-style header declaration, ensuring both the pipeline and bind group agree
    // on the types of resources.
    let bind_group_layout = device.create_bind_group_layout(&wgpu::BindGroupLayoutDescriptor {
        label: None,
        entries: &[
            // Input buffer
            wgpu::BindGroupLayoutEntry {
                binding: 0,
                visibility: wgpu::ShaderStages::COMPUTE,
                ty: wgpu::BindingType::Buffer {
                    ty: wgpu::BufferBindingType::Storage { read_only: true },
                    // This is the size of a single element in the buffer.
                    min_binding_size: Some(NonZeroU64::new(512).unwrap()),
                    has_dynamic_offset: false,
                },
                count: None,
            },
            wgpu::BindGroupLayoutEntry {
                binding: 1, 
                visibility: wgpu::ShaderStages::COMPUTE,
                ty: wgpu::BindingType::Buffer {
                    ty: wgpu::BufferBindingType::Storage { read_only: true },
                    // This is the size of a single element in the buffer.
                    min_binding_size: Some(NonZeroU64::new(4).unwrap()),
                    has_dynamic_offset: false,
                },
                count: None,
            },
        
            // Output buffer
            wgpu::BindGroupLayoutEntry {
                binding: 2,
                visibility: wgpu::ShaderStages::COMPUTE,
                ty: wgpu::BindingType::Buffer {
                    ty: wgpu::BufferBindingType::Storage { read_only: false },
                    // This is the size of a single element in the buffer.
                    min_binding_size: Some(NonZeroU64::new(32).unwrap()),
                    has_dynamic_offset: false,
                },
                count: None,
            },
        ],
    });

    // The bind group contains the actual resources to bind to the pipeline.
    //
    // Even when the buffers are individually dropped, wgpu will keep the bind group and buffers
    // alive until the bind group itself is dropped.
    let bind_group = device.create_bind_group(&wgpu::BindGroupDescriptor {
        label: None,
        layout: &bind_group_layout,
        entries: &[
            wgpu::BindGroupEntry {
                binding: 0,
                resource: input_data_buffer.as_entire_binding(),
            },
            wgpu::BindGroupEntry {
                binding: 1,
                resource: data_size_buffer.as_entire_binding(),
            },
            wgpu::BindGroupEntry {
                binding: 2,
                resource: output_data_buffer.as_entire_binding(),
            },
        ],
    });

    // The pipeline layout describes the bind groups that a pipeline expects
    let pipeline_layout = device.create_pipeline_layout(&wgpu::PipelineLayoutDescriptor {
        label: None,
        bind_group_layouts: &[&bind_group_layout],
        immediate_size: 0,
    });

    // The pipeline is the ready-to-go program state for the GPU. It contains the shader modules,
    // the interfaces (bind group layouts) and the shader entry point.
    let pipeline = device.create_compute_pipeline(&wgpu::ComputePipelineDescriptor {
        label: None,
        layout: Some(&pipeline_layout),
        module: &module,
        entry_point: Some("main"),
        compilation_options: wgpu::PipelineCompilationOptions::default(),
        cache: None,
    });

        
    let mut nibbles: [u16; OUTPUT_SIZE as usize/ 8] = [0;4];
    let mut b = bits as u16; 
    for n in 0..4 {
        if b > 64 {
            nibbles[n] = 64;
            b -= 64;
        } else {
            nibbles[n] = b; 
            break;
        }
    }

    // == Begin repeating part 
    let mut found: Option<[u8;32]> = None; 
    let mut found_input: Option<String> = None;
    let mut nonces_1: Vec<NonceElement>= Vec::with_capacity(BATCH_SIZE as usize);
    let mut nonces_2: Vec<NonceElement>= Vec::with_capacity(BATCH_SIZE as usize);
    let mut nonce_bufs = (nonces_1, nonces_2); 
    let mut prev_time: Instant = Instant::now(); 
    let mut prev_submission_index = None; 
    println!("starting!");
    for x in 0 .. MAX_ITER {
        let data_upload_buffer = device.create_buffer(&wgpu::BufferDescriptor {
            label: Some("Upload Data"),
            size: INPUT_BUF_SIZE,
            usage: wgpu::BufferUsages::COPY_SRC | wgpu::BufferUsages::MAP_WRITE,
            mapped_at_creation: true,
        });
        let size_upload_buffer = device.create_buffer(&wgpu::BufferDescriptor {
            label: Some("Upload Size"),
            size: SIZES_BUF_SIZE,
            usage: wgpu::BufferUsages::COPY_SRC | wgpu::BufferUsages::MAP_WRITE,
            mapped_at_creation: true,
        });
        let mut input_slice = data_upload_buffer.get_mapped_range_mut(..); 
        let mut len_slice   = size_upload_buffer.get_mapped_range_mut(..); 

        let nonces = swaptuple_get_mut(&mut nonce_bufs, x);
        for i in 0 .. BATCH_SIZE {
          if let Some(element) = iter.next() {
              let inputdata = element.to_hash_input(&value, &prev).into_bytes(); 
              let inputlen  = inputdata.len() as u32;
              let lenbytes  = inputlen.to_le_bytes(); 
             
              // println!("{}: {}, {}", i, inputlen*8, str::from_utf8(&inputdata).unwrap());
              input_slice[(i * INPUT_SIZE) as usize .. (i*INPUT_SIZE + inputlen as u64) as usize].copy_from_slice(&inputdata);
              len_slice[(i * INSIZE_SIZE) as usize .. ((i+1) * INSIZE_SIZE) as usize].copy_from_slice(&lenbytes);
              // println!("In data {:?}", &input_slice[(i * INPUT_SIZE) as usize .. (i*INPUT_SIZE + inputlen as u64) as usize]);
              // println!("In length {:?}", &len_slice[(i * INSIZE_SIZE) as usize .. ((i+1) * INSIZE_SIZE) as usize]);
              nonces.push(element);
          } else {
                panic!("Infinite iter died")
          }
        }
        // println!("Hex slice:\n{}", hex::encode(&input_slice[..]));
        drop(input_slice);       // The command encoder allows us to record commands that we will later submit to the GPU.
        drop(len_slice); 
        data_upload_buffer.unmap();
        size_upload_buffer.unmap();

        let mut encoder =
            device.create_command_encoder(&wgpu::CommandEncoderDescriptor { label: None });
         
        // We add a copy operation to the encoder. This will copy the data from the output buffer on the
        // GPU to the download buffer on the CPU.
        encoder.copy_buffer_to_buffer(
            &data_upload_buffer,
            0,
            &input_data_buffer,
            0,
            data_upload_buffer.size(),
        );
        encoder.copy_buffer_to_buffer(
            &size_upload_buffer,
            0,
            &data_size_buffer,
            0,
            size_upload_buffer.size(),
        );

        // A compute pass is a single series of compute operations. While we are recording a compute
        // pass, we cannot record to the encoder.
        let mut compute_pass = encoder.begin_compute_pass(&wgpu::ComputePassDescriptor {
            label: None,
            timestamp_writes: None,
        });

        // Set the pipeline that we want to use
        compute_pass.set_pipeline(&pipeline);
        // Set the bind group that we want to use
        compute_pass.set_bind_group(0, &bind_group, &[]);

        // Now we dispatch a series of workgroups. Each workgroup is a 3D grid of individual programs.
        //
        // We defined the workgroup size in the shader as 64x1x1. So in order to process all of our
        // inputs, we ceiling divide the number of inputs by 64. If the user passes 32 inputs, we will
        // dispatch 1 workgroups. If the user passes 65 inputs, we will dispatch 2 workgroups, etc.
        
        let rest = BATCH_SIZE % 64; 
        let mut workgroup_count = BATCH_SIZE - rest / 64;
        if rest > 0  {
            workgroup_count += 1;
        }
        compute_pass.dispatch_workgroups(workgroup_count as u32, 1, 1);

        // Now we drop the compute pass, giving us access to the encoder again.
        drop(compute_pass);

        // We add a copy operation to the encoder. This will copy the data from the output buffer on the
        // GPU to the download buffer on the CPU.
        encoder.copy_buffer_to_buffer(
            &output_data_buffer,
            0,
            swaptuple_get(&dl_bufs, x),
            0,
            output_data_buffer.size(),
        );

        // We finish the encoder, giving us a fully recorded command buffer.
        let command_buffer = encoder.finish();


        
        let sub_index = queue.submit([command_buffer]);
        // println!("A pass has been submitted");
        // Wait for the GPU to finish working on the submitted work. This doesn't work on WebGPU, so we would need
        // to rely on the callback to know when the buffer is mapped.
        
        if x > 0 {
            let nonces = swaptuple_get_mut(&mut nonce_bufs, x -1);
            let download_buffer = swaptuple_get(&dl_bufs, x-1); 
            let buffer_slice = download_buffer.slice(..);
            buffer_slice.map_async(wgpu::MapMode::Read, |_| {});
            device.poll(wgpu::PollType::Wait { submission_index: prev_submission_index, timeout: None }).unwrap();
            // In this case we know exactly when the mapping will be finished,
            // so we don't need to do anything in the callback.
            let data = buffer_slice.get_mapped_range();
            // println!("Out data {:?}", &data[..]);
            // println!("Out hash {:?}", hex::encode(&data[..]));
            let results: &[u8] = bytemuck::cast_slice(&data[..]);
            
            // println!("Full buffer: {}", hex::encode(results) );
            for i in 0..(BATCH_SIZE as usize) {
                let result: &[u8;32] = &results[32*i..32*(i+1)].try_into().unwrap();  
                // println!("Hash of {}, {}", hex::encode(nonces.get(i).unwrap().bytes.clone()), hex::encode(bytemuck::cast_slice(result)));
                let mut correct = true; 
                for n in 0..4 {
                    if u64::from_be_bytes(result[n*8..(n+1)*8].try_into().unwrap()).leading_zeros() < nibbles[n] as u32{
                        correct = false; 
                        break;
                    }
                }
                if correct {
                    found = Some(*result);
                    let nonce = nonces.get(i).expect("We pushed all those nonces, right?").bytes.clone(); 
                    found_input = Some(String::from_utf8(nonce).unwrap());
                    // break;
                }
            }
            if found.is_some() {
                break;
            }
            drop(data);
            download_buffer.unmap();
            nonces.clear();
            let now = Instant::now(); 
            let delta = (now - prev_time).as_secs_f64(); 
            let hashrate = BATCH_SIZE as f64 / delta; 
             println!("\x1b[A\rFinished batch {}, {} hashes processed ({:.2} H/s) (delta: {}) ", x + 1, x * BATCH_SIZE, hashrate, delta);
            prev_time = Instant::now(); 
        }
        prev_submission_index = Some(sub_index); 
     
    }

    match found {
        Some(f) => {
            let hashbytes: &[u8] = bytemuck::cast_slice(&f);
            let nonce  = found_input.unwrap();
            println!("Found! {:?}", hex::encode(hashbytes));
            println!("Full block: {}{}{}", value, prev , nonce);
            println!("Nonce: \"{}\"", nonce);
        }
        None => {
            println!("Could not find a valid hash")
        }
    }



    println!("Done for now")


}