WebAssembly Threads

What Are WebAssembly Threads?

Threads in WebAssembly allow a program to execute multiple parts of its code concurrently. Each thread operates within the same memory space, enabling efficient communication and data sharing. WebAssembly Threads are implemented using Web Workers in JavaScript and rely on the SharedArrayBuffer to manage shared memory between threads.

Why Use WebAssembly Threads?

1. Performance Enhancement:
   By utilizing multiple CPU cores, threads can significantly improve the speed of computation-heavy tasks.
2. Real-Time Processing:
   Applications like video games and real-time simulations benefit from threads by ensuring smooth and responsive performance.
3. Efficient Resource Utilization:
   Threads maximize the use of modern multi-core processors, improving overall efficiency.
4. Parallel Data Processing:
   Suitable for tasks like image processing, matrix operations and machine learning model inference.

Components of WebAssembly Threads

1. Shared Memory:
   Threads use a SharedArrayBuffer to access a common memory space, eliminating the need for duplicating data between threads.
2. Web Workers:
   Web Workers are used in JavaScript to spawn threads and run WebAssembly code concurrently.
3. Atomic Operations:
   To ensure safe data manipulation, WebAssembly provides atomic instructions like atomic.add, atomic.store and atomic.load.

Setting Up WebAssembly Threads

Requirements

Cross-Origin Isolation:
To use SharedArrayBuffer, enable cross-origin isolation on your server:

Cross-Origin-Opener-Policy: same-origin
Cross-Origin-Embedder-Policy: require-corp

Browser Support:
Ensure that the browser supports SharedArrayBuffer and Web Workers.

Practical Example of WebAssembly Threads

Use Case: Parallel Matrix Multiplication

We will multiply two large matrices in parallel using WebAssembly Threads.

WebAssembly Code (matrix.wat):

(module
  (memory (export "memory") 1)
  (func $multiply (param $a i32) (param $b i32) (param $c i32) (param $n i32)
    (local $i i32) 
    (local $j i32)
    (local $k i32)
    (local $sum i32)
    (loop $outer
      local.get $i
      local.get $n
      i32.ge_s
      if (result i32)
        return
      end
      local.set $j
      (loop $inner
        local.get $j
        local.get $n
        i32.ge_s
        if (result i32)
          br $outer
        end
        local.set $sum
        (loop $innermost
          local.get $k
          local.get $n
          i32.ge_s
          if (result i32)
            br $inner
          end
          ;; Matrix multiplication logic
          local.get $sum
          local.get $a
          local.get $i
          local.get $k
          i32.mul
          i32.load
          local.get $b
          local.get $k
          local.get $j
          i32.mul
          i32.load
          i32.add
          local.set $sum
          local.get $k
          i32.const 1
          i32.add
          local.set $k
        )
        ;; Store the result
        local.get $c
        local.get $i
        local.get $j
        i32.mul
        local.get $sum
        i32.store
        local.get $j
        i32.const 1
        i32.add
        local.set $j
      )
      local.get $i
      i32.const 1
      i32.add
      local.set $i
      br $outer
    )
  )
  (export "multiply" (func $multiply))
)

JavaScript Code for Web Workers

1. Main JavaScript File:

async function initWasm() {
  const response = await fetch("matrix.wasm");
  const buffer = await response.arrayBuffer();
  const { instance } = await WebAssembly.instantiate(buffer);
  return instance;
}

async function main() {
  const wasmInstance = await initWasm();

  // Matrix dimensions
  const n = 1000;
  const matrixA = new Int32Array(new SharedArrayBuffer(n * n * 4));
  const matrixB = new Int32Array(new SharedArrayBuffer(n * n * 4));
  const matrixC = new Int32Array(new SharedArrayBuffer(n * n * 4));

  // Initialize matrices
  for (let i = 0; i < n * n; i++) {
    matrixA[i] = Math.random() * 10;
    matrixB[i] = Math.random() * 10;
  }

  // Divide work into threads
  const workers = [];
  const chunkSize = n / 4; // Divide into 4 chunks

  for (let i = 0; i < 4; i++) {
    const worker = new Worker("worker.js");
    worker.postMessage({
      wasmInstance,
      matrixA,
      matrixB,
      matrixC,
      start: i * chunkSize,
      end: (i + 1) * chunkSize,
      n,
    });
    workers.push(new Promise((resolve) => {
      worker.onmessage = () => resolve();
    }));
  }

  await Promise.all(workers);

  console.log("Matrix multiplication complete.");
}
main();

2. Worker File (worker.js):

onmessage = ({ data }) => {
  const { wasmInstance, matrixA, matrixB, matrixC, start, end, n } = data;
  const multiply = wasmInstance.exports.multiply;
  multiply(matrixA.byteOffset, matrixB.byteOffset, matrixC.byteOffset, n, start, end);
  postMessage("done");
};

Benefits of WebAssembly Threads

1. Performance Gains:
   Tasks like matrix multiplication and simulations run significantly faster with multiple threads.
2. Real-Time Updates:
   Critical for applications like video games and financial modeling.
3. Resource Sharing:
   Shared memory allows efficient communication between threads.

Challenges with WebAssembly Threads

1. Complex Debugging:
   Thread-related bugs like race conditions and deadlocks can be challenging to diagnose.
2. Cross-Origin Restrictions:
   The need for cross-origin isolation adds an extra configuration step.
3. Synchronization Overhead:
   Incorrect usage of atomic operations can lead to performance bottlenecks.

Debugging Threads in WebAssembly

1. Logging:
   Add detailed logs for thread creation and execution.
2. Atomic Debugging:
   Monitor atomic operations to ensure proper synchronization.
3. Browser Tools:
   Use browser DevTools to debug Web Workers and shared memory usage.