webgpu

package
v0.5.5 Latest Latest
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 Go to latest Published: Dec 3, 2025 License: Apache-2.0 Imports: 7 Imported by: 0

Documentation

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Overview

Package webgpu implements the WebGPU backend for GPU-accelerated tensor operations. Uses go-webgpu (github.com/go-webgpu/webgpu) for zero-CGO WebGPU bindings.

Package webgpu provides embedded WGSL compute shaders for tensor operations.

Index

Constants

This section is empty.

Variables

This section is empty.

Functions

func IsAvailable 

func IsAvailable() (available bool)

IsAvailable checks if WebGPU is available on this system.

func ListAdapters 

func ListAdapters() (adapters []*wgpu.AdapterInfoGo, err error)

ListAdapters returns information about all available GPU adapters.

Types

type Backend 

type Backend struct {
	// contains filtered or unexported fields
}

Backend implements tensor operations on GPU using WebGPU.

func New 

func New() (backend *Backend, err error)

New creates a new WebGPU backend. Returns an error if WebGPU is not available or initialization fails.

func (*Backend) AdapterInfo 

func (b *Backend) AdapterInfo() *wgpu.AdapterInfoGo

AdapterInfo returns information about the GPU adapter.

func (*Backend) Add 

func (b *Backend) Add(a, other *tensor.RawTensor) *tensor.RawTensor

Add performs element-wise addition on GPU. Supports float32 and int32 dtypes.

func (*Backend) AddScalar added in v0.3.0 

func (b *Backend) AddScalar(x *tensor.RawTensor, scalar any) *tensor.RawTensor

AddScalar adds a scalar to tensor elements on GPU.

func (*Backend) And added in v0.3.0 

func (b *Backend) And(a, other *tensor.RawTensor) *tensor.RawTensor

And performs element-wise logical AND on GPU. Supports mixed dtypes by casting to float32 (for boolean tensors from different sources).

func (*Backend) Argmax added in v0.3.0 

func (b *Backend) Argmax(x *tensor.RawTensor, dim int) *tensor.RawTensor

Argmax returns indices of maximum values along dimension on GPU.

func (*Backend) BatchMatMul added in v0.4.0 

func (b *Backend) BatchMatMul(a, other *tensor.RawTensor) *tensor.RawTensor

BatchMatMul performs batched matrix multiplication on GPU. Supports 3D tensors [batch, M, K] @ [batch, K, N] -> [batch, M, N] and 4D tensors [batch, heads, M, K] @ [batch, heads, K, N].

func (*Backend) Cast added in v0.3.0 

func (b *Backend) Cast(x *tensor.RawTensor, dtype tensor.DataType) *tensor.RawTensor

Cast converts tensor to different data type. Supports float32 and int32 as target types.

func (*Backend) Cat added in v0.3.0 

func (b *Backend) Cat(tensors []*tensor.RawTensor, dim int) *tensor.RawTensor

Cat concatenates tensors along the specified dimension.

func (*Backend) Chunk added in v0.3.0 

func (b *Backend) Chunk(x *tensor.RawTensor, n, dim int) []*tensor.RawTensor

Chunk splits tensor into n equal parts along the specified dimension.

func (*Backend) Conv2D 

func (b *Backend) Conv2D(input, kernel *tensor.RawTensor, stride, padding int) *tensor.RawTensor

Conv2D performs 2D convolution on GPU. Input shape: [batch, in_channels, height, width]. Kernel shape: [out_channels, in_channels, kH, kW].

func (*Backend) Cos added in v0.3.0 

func (b *Backend) Cos(x *tensor.RawTensor) *tensor.RawTensor

Cos computes element-wise cosine on GPU.

func (*Backend) Device 

func (b *Backend) Device() tensor.Device

Device returns the compute device.

func (*Backend) Div 

func (b *Backend) Div(a, other *tensor.RawTensor) *tensor.RawTensor

Div performs element-wise division on GPU. Supports float32 and int32 dtypes.

func (*Backend) DivScalar added in v0.3.0 

func (b *Backend) DivScalar(x *tensor.RawTensor, scalar any) *tensor.RawTensor

DivScalar divides tensor elements by a scalar on GPU.

func (*Backend) Embedding added in v0.5.1 

func (b *Backend) Embedding(weight, indices *tensor.RawTensor) *tensor.RawTensor

Embedding performs embedding lookup on GPU. weight: [num_embeddings, embedding_dim], indices: int32 tensor. Returns: [...indices_shape, embedding_dim].

func (*Backend) Equal added in v0.3.0 

func (b *Backend) Equal(a, other *tensor.RawTensor) *tensor.RawTensor

Equal performs element-wise equality comparison on GPU. Always returns float32 tensor (0.0 for false, 1.0 for true).

func (*Backend) Exp added in v0.3.0 

func (b *Backend) Exp(x *tensor.RawTensor) *tensor.RawTensor

Exp computes element-wise exponential on GPU.

func (*Backend) Expand added in v0.3.0 

func (b *Backend) Expand(x *tensor.RawTensor, newShape tensor.Shape) *tensor.RawTensor

Expand broadcasts tensor to new shape. GPU-accelerated for up to 6D tensors.

func (*Backend) Gather added in v0.3.0 

func (b *Backend) Gather(input *tensor.RawTensor, dim int, indices *tensor.RawTensor) *tensor.RawTensor

Gather selects elements along dim using index tensor on GPU.

func (*Backend) Greater added in v0.3.0 

func (b *Backend) Greater(a, other *tensor.RawTensor) *tensor.RawTensor

Greater performs element-wise greater-than comparison on GPU. Always returns float32 tensor (0.0 for false, 1.0 for true).

func (*Backend) GreaterEqual added in v0.3.0 

func (b *Backend) GreaterEqual(a, other *tensor.RawTensor) *tensor.RawTensor

GreaterEqual performs element-wise greater-or-equal comparison on GPU. Always returns float32 tensor (0.0 for false, 1.0 for true).

func (*Backend) Log added in v0.3.0 

func (b *Backend) Log(x *tensor.RawTensor) *tensor.RawTensor

Log computes natural logarithm element-wise on GPU.

func (*Backend) Lower added in v0.3.0 

func (b *Backend) Lower(a, other *tensor.RawTensor) *tensor.RawTensor

Lower performs element-wise less-than comparison on GPU. Always returns float32 tensor (0.0 for false, 1.0 for true).

func (*Backend) LowerEqual added in v0.3.0 

func (b *Backend) LowerEqual(a, other *tensor.RawTensor) *tensor.RawTensor

LowerEqual performs element-wise less-or-equal comparison on GPU. Always returns float32 tensor (0.0 for false, 1.0 for true).

func (*Backend) MatMul 

func (b *Backend) MatMul(a, other *tensor.RawTensor) *tensor.RawTensor

MatMul performs matrix multiplication on GPU.

func (*Backend) MaxPool2D 

func (b *Backend) MaxPool2D(input *tensor.RawTensor, kernelSize, stride int) *tensor.RawTensor

MaxPool2D performs 2D max pooling on GPU. Input shape: [batch, channels, height, width].

func (*Backend) MeanDim added in v0.3.0 

func (b *Backend) MeanDim(x *tensor.RawTensor, dim int, keepDim bool) *tensor.RawTensor

MeanDim computes mean along a dimension.

func (*Backend) MemoryStats 

func (b *Backend) MemoryStats() MemoryStats

MemoryStats returns current GPU memory usage statistics.

func (*Backend) Mul 

func (b *Backend) Mul(a, other *tensor.RawTensor) *tensor.RawTensor

Mul performs element-wise multiplication on GPU. Supports float32 and int32 dtypes.

func (*Backend) MulScalar added in v0.3.0 

func (b *Backend) MulScalar(x *tensor.RawTensor, scalar any) *tensor.RawTensor

MulScalar multiplies tensor elements by a scalar on GPU.

func (*Backend) Name 

func (b *Backend) Name() string

Name returns the backend name.

func (*Backend) Not added in v0.3.0 

func (b *Backend) Not(x *tensor.RawTensor) *tensor.RawTensor

Not performs element-wise logical NOT on GPU.

func (*Backend) NotEqual added in v0.3.0 

func (b *Backend) NotEqual(a, other *tensor.RawTensor) *tensor.RawTensor

NotEqual performs element-wise inequality comparison on GPU. Always returns float32 tensor (0.0 for false, 1.0 for true).

func (*Backend) Or added in v0.3.0 

func (b *Backend) Or(a, other *tensor.RawTensor) *tensor.RawTensor

Or performs element-wise logical OR on GPU. Supports mixed dtypes by casting to float32 (for boolean tensors from different sources).

func (*Backend) ReLU 

func (b *Backend) ReLU(x *tensor.RawTensor) *tensor.RawTensor

ReLU applies ReLU activation: max(0, x).

func (*Backend) Release 

func (b *Backend) Release()

Release releases all WebGPU resources. Must be called when the backend is no longer needed.

func (*Backend) Reshape 

func (b *Backend) Reshape(t *tensor.RawTensor, newShape tensor.Shape) *tensor.RawTensor

Reshape returns a tensor with new shape. This is typically a metadata-only operation (zero-copy).

func (*Backend) Rsqrt added in v0.3.0 

func (b *Backend) Rsqrt(x *tensor.RawTensor) *tensor.RawTensor

Rsqrt computes element-wise reciprocal square root on GPU.

func (*Backend) Sigmoid 

func (b *Backend) Sigmoid(x *tensor.RawTensor) *tensor.RawTensor

Sigmoid applies sigmoid activation: 1 / (1 + exp(-x)).

func (*Backend) Sin added in v0.3.0 

func (b *Backend) Sin(x *tensor.RawTensor) *tensor.RawTensor

Sin computes element-wise sine on GPU.

func (*Backend) Softmax 

func (b *Backend) Softmax(x *tensor.RawTensor, dim int) *tensor.RawTensor

Softmax applies softmax along the specified dimension. Supports N-dimensional tensors with dim=-1 (last dimension).

func (*Backend) Sqrt added in v0.3.0 

func (b *Backend) Sqrt(x *tensor.RawTensor) *tensor.RawTensor

Sqrt computes element-wise square root on GPU.

func (*Backend) Squeeze added in v0.3.0 

func (b *Backend) Squeeze(x *tensor.RawTensor, dim int) *tensor.RawTensor

Squeeze removes a dimension of size 1 at the specified position.

func (*Backend) Sub 

func (b *Backend) Sub(a, other *tensor.RawTensor) *tensor.RawTensor

Sub performs element-wise subtraction on GPU. Supports float32 and int32 dtypes.

func (*Backend) SubScalar added in v0.3.0 

func (b *Backend) SubScalar(x *tensor.RawTensor, scalar any) *tensor.RawTensor

SubScalar subtracts a scalar from tensor elements on GPU.

func (*Backend) Sum added in v0.3.0 

func (b *Backend) Sum(x *tensor.RawTensor) *tensor.RawTensor

Sum computes the sum of all elements on GPU.

func (*Backend) SumDim added in v0.3.0 

func (b *Backend) SumDim(x *tensor.RawTensor, dim int, keepDim bool) *tensor.RawTensor

SumDim sums along a dimension. Implemented on CPU as reduction operations are complex on GPU.

func (*Backend) Tanh 

func (b *Backend) Tanh(x *tensor.RawTensor) *tensor.RawTensor

Tanh applies tanh activation.

func (*Backend) Transpose 

func (b *Backend) Transpose(t *tensor.RawTensor, axes ...int) *tensor.RawTensor

Transpose transposes the tensor by permuting its dimensions. GPU-accelerated for 2D (optimized) and ND tensors (up to 6D).

func (*Backend) Unsqueeze added in v0.3.0 

func (b *Backend) Unsqueeze(x *tensor.RawTensor, dim int) *tensor.RawTensor

Unsqueeze adds a dimension of size 1 at the specified position.

func (*Backend) Where added in v0.3.0 

func (b *Backend) Where(condition, x, y *tensor.RawTensor) *tensor.RawTensor

Where performs conditional element selection on GPU. result[i] = condition[i] != 0 ? x[i] : y[i].

type BufferPool 

type BufferPool struct {
	// contains filtered or unexported fields
}

BufferPool manages GPU buffer reuse to reduce allocation overhead. Buffers are categorized by size and usage flags.

func NewBufferPool 

func NewBufferPool(device *wgpu.Device) *BufferPool

NewBufferPool creates a new buffer pool for the given device.

func (*BufferPool) Acquire 

func (p *BufferPool) Acquire(size uint64, usage wgpu.BufferUsage) *wgpu.Buffer

Acquire gets a buffer from the pool or creates a new one. Returns a buffer that matches or exceeds the requested size and usage.

func (*BufferPool) Clear 

func (p *BufferPool) Clear()

Clear releases all pooled buffers. Should be called when the backend is released.

func (*BufferPool) Release 

func (p *BufferPool) Release(buffer *wgpu.Buffer, size uint64, usage wgpu.BufferUsage)

Release returns a buffer to the pool for reuse. If the pool is full, the buffer is immediately released.

func (*BufferPool) Stats 

func (p *BufferPool) Stats() (allocated, released, hits, misses uint64, pooledCount int)

Stats returns statistics about buffer pool usage.

type BufferSize 

type BufferSize int

BufferSize represents different buffer size categories for pooling. 

const (
	// SmallBuffer for tensors < 4KB.
	SmallBuffer BufferSize = iota
	// MediumBuffer for tensors 4KB-1MB.
	MediumBuffer
	// LargeBuffer for tensors > 1MB.
	LargeBuffer
)

type MemoryStats 

type MemoryStats struct {
	// Total bytes allocated since backend creation
	TotalAllocatedBytes uint64
	// Peak memory usage in bytes
	PeakMemoryBytes uint64
	// Number of currently active buffers
	ActiveBuffers int64
	// Buffer pool statistics
	PoolAllocated uint64
	PoolReleased  uint64
	PoolHits      uint64
	PoolMisses    uint64
	PooledBuffers int
}

MemoryStats represents GPU memory usage statistics.

Source Files

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