Update README

README.md

@@ -1,3 +1,5 @@
+Here is the minimal README for the library, completely free of any citations or source references.
+
 # Minimal Zig WebGPU Compute Library
 
 This is a minimal, self-contained Zig library designed to simplify running compute shaders using WebGPU. It abstracts away much of the boilerplate required for GPU device initialization, memory management, and pipeline execution.
@@ -6,21 +8,10 @@ This is a minimal, self-contained Zig library designed to simplify running compu
 
 The library exports five primary components:
 
-* 
-**`GpuDevice`**: Initializes the WebGPU instance, adapter, device, and queue. It is configured to prioritize high performance and automatically requests the `ShaderF16` feature if the adapter supports it. By default, it enforces a 2 GB VRAM limit.
-
-
-* 
-**`GpuArena` / `GpuAllocator**`: A memory management layer that tracks allocated VRAM bytes to prevent exceeding the device budget. The arena automatically destroys and releases all tracked WebGPU buffers when deinitialized.
-
-
+* **`GpuDevice`**: Initializes the WebGPU instance, adapter, device, and queue. It is configured to prioritize high performance and automatically requests the `ShaderF16` feature if the adapter supports it. By default, it enforces a 2 GB VRAM limit.
+* **`GpuArena` / `GpuAllocator`**: A memory management layer that tracks allocated VRAM bytes to prevent exceeding the device budget. The arena automatically destroys and releases all tracked WebGPU buffers when deinitialized.
 * **`GpuBuffer`**: Wraps native WebGPU buffers. It automatically aligns buffer sizes forward to a multiple of 4 bytes. It provides a `.load()` method for CPU-to-GPU data transfers (handling both aligned and unaligned lengths smoothly) and a `.read()` method that utilizes a staging buffer to map GPU data back to the CPU.
-
-
-* 
-**`GpuProcess`**: Compiles WGSL source code into a compute pipeline. When running a process, it automatically splits the work into manageable chunks (up to 1 GB at a time) and dispatches workgroups of size 256.
-
-
+* **`GpuProcess`**: Compiles WGSL source code into a compute pipeline. When running a process, it automatically splits the work into manageable chunks (up to 1 GB at a time) and dispatches workgroups of size 256.
 
 ## Quick Start Example
 
@@ -36,20 +27,20 @@ const GpuProcess = @import("GpuProcess.zig");
 pub fn main(init: std.process.Init) !void {
     const allocator = init.gpa;
 
-    [cite_start]// 1. Open GPU Device [cite: 46]
+    // 1. Open GPU Device
     const device = try GpuDevice.init(.{});
     defer device.deinit();
 
-    [cite_start]// 2. Create a GPU Arena to hold GPU memory [cite: 47]
+    // 2. Create a GPU Arena to hold GPU memory
     var grena = GpuArena.init(allocator, device);
     defer grena.deinit();
-    [cite_start]const gloc = grena.gpuAllocator(); [cite: 48]
+    const gloc = grena.gpuAllocator();
 
-    [cite_start]// 3. Create a GPU process that loads the WGSL pipeline/shader [cite: 48]
+    // 3. Create a GPU process that loads the WGSL pipeline/shader
     const add = try GpuProcess.init(device, @embedFile("shaders/add.wgsl"));
-    [cite_start]defer add.deinit(); [cite: 49]
+    defer add.deinit();
 
-    [cite_start]// 4. Allocate and populate CPU memory [cite: 49, 50, 51]
+    // 4. Allocate and populate CPU memory
     const data_a = try allocator.alloc(f16, 16);
     defer allocator.free(data_a);
     const data_b = try allocator.alloc(f16, 16);
@@ -60,27 +51,26 @@ pub fn main(init: std.process.Init) !void {
         data_b[i] = @floatFromInt(16 - 1 - i);
     }
 
-    [cite_start]// 5. Allocate GPU memory (deinit handled automatically by grena) [cite: 52]
+    // 5. Allocate GPU memory (deinit handled automatically by grena)
     const a = try Vec.initZero(gloc, 16);
-    [cite_start]const b = try Vec.initZero(gloc, 16); [cite: 53]
+    const b = try Vec.initZero(gloc, 16);
 
-    [cite_start]// 6. Load CPU -> GPU [cite: 53]
+    // 6. Load CPU -> GPU
     try a.load(data_a);
     try b.load(data_b);
 
-    [cite_start]// 7. Run GPU Pipeline [cite: 54]
+    // 7. Run GPU Pipeline
     const sum = try a.run(gloc, b, add);
 
-    [cite_start]// 8. Read GPU -> CPU [cite: 55]
+    // 8. Read GPU -> CPU
     const out = try sum.read(allocator);
     defer allocator.free(out);
 
-    [cite_start]std.debug.print("{any}\n", .{out}); [cite: 55]
+    std.debug.print("{any}\n", .{out});
 }
 
 ```
 
 ## Dependencies
 
-* 
-**`wgpu.h`**: The library relies on the WebGPU C API headers to bind to the native system graphics.
+* **`wgpu.h`**: The library relies on the WebGPU C API headers to bind to the native system graphics.