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Copy pathop_math_cuda.go
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op_math_cuda.go
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// +build cuda
package gorgonia
import (
"fmt"
"unsafe"
"github.com/pkg/errors"
"gorgonia.org/cu"
"gorgonia.org/gorgonia/cuda"
"gorgonia.org/tensor"
)
// module names
const (
elemBinOpMod = "elembinop"
elemUnaryOpMod = "elemunaryop"
)
func (op elemUnaryOp) CallsExtern() bool { return true }
func (op elemUnaryOp) CUDADo(extern External, dev Device, prealloc Value, inputs ...Value) (retVal Value, err error) {
if err = checkArity(op, len(inputs)); err != nil {
return
}
cudaLogf("CUDADoing %v | prealloc %x | %x", op, prealloc.Uintptr(), inputs[0].Uintptr())
enterLogScope()
defer leaveLogScope()
// check
cudaLogf("checking if input is scalar")
a := inputs[0]
dt := a.Dtype()
// build name
name := fmt.Sprintf("%v.%v_f%d", elemUnaryOpMod, op.unaryOpType(), int(dt.Size())*8)
machine := extern.(CUDAMachine)
eng := machine.Engines()[int(dev)]
if !eng.HasFunc(name) {
cudaLogf("extern does not have func %q", name)
extern.Signal()
if retVal, err = op.do(a); err != nil {
return
}
if prealloc == nil {
return
}
return Copy(prealloc, retVal)
}
fn := eng.Functions()[name]
ctx := machine.Contexts()[int(dev)]
retVal = prealloc
if prealloc == nil {
prealloc = a
retVal = a
}
var mem cu.DevicePtr
if prealloc.Uintptr() == a.Uintptr() && a.Shape().Eq(prealloc.Shape()) {
mem = cu.DevicePtr(a.Uintptr())
} else {
mem = cu.DevicePtr(prealloc.Uintptr())
memSize := int64(a.MemSize())
memA := cu.DevicePtr(a.Uintptr())
ctx.Memcpy(mem, memA, memSize)
}
size := logicalSize(a.Shape())
// blocks, threads := machine.(*tapeMachine).blockThread(int(size), int(dev))
gridDimX, gridDimY, gridDimZ, blockDimX, blockDimY, blockDimZ := machine.ElemGridSize(int(size), int(dev))
args := []unsafe.Pointer{
unsafe.Pointer(&mem),
unsafe.Pointer(&size),
}
cudaLogf("gx %d, gy %d, gz %d | bx %d by %d, bz %d", gridDimX, gridDimY, gridDimZ, blockDimX, blockDimY, blockDimZ)
cudaLogf("CUDADO %q, Mem: %v size %v, args %v", name, mem, size, args)
cudaLogf("LaunchKernel Params. mem: %v. Size %v", mem, size)
ctx.LaunchAndSync(fn, gridDimX, gridDimY, gridDimZ, blockDimX, blockDimY, blockDimZ, 0, cu.NoStream, args)
return
}
func (op elemBinOp) CallsExtern() bool { return true }
func (op elemBinOp) CUDADo(extern External, dev Device, prealloc Value, inputs ...Value) (retVal Value, err error) {
if err = checkArity(op, len(inputs)); err != nil {
return
}
cudaLogf("CUDADoing %v", op)
enterLogScope()
defer leaveLogScope()
a := inputs[0]
b := inputs[1]
as := a.Shape()
bs := b.Shape()
m := extern.(CUDAMachine)
e := &m.Engines()[int(dev)]
if as.IsScalar() && bs.IsScalar() {
return op.ssop(a, b, prealloc, e)
}
if aT, ok := a.(tensor.Tensor); ok {
tensor.WithEngine(e)(aT)
}
if bT, ok := b.(tensor.Tensor); ok {
tensor.WithEngine(e)(bT)
}
pT, toReuse := prealloc.(tensor.Tensor)
if toReuse {
tensor.WithEngine(e)(pT)
}
boType := op.binOpType()
if fn := binOps[boType]; fn != nil {
if toReuse {
return (*fn)(a, b, tensor.WithReuse(pT))
} else {
return (*fn)(a, b, tensor.UseUnsafe())
}
}
if fn := cmpOps[boType]; fn != nil {
if toReuse {
return (*fn)(a, b, tensor.WithReuse(pT))
} else {
return (*fn)(a, b, tensor.UseUnsafe())
}
}
return nil, errors.Errorf("op %v cannot be done by CUDA", op)
}
func (op elemBinOp) ssop(a, b, prealloc Value, e *cuda.Engine) (retVal Value, err error) {
dt := a.Dtype()
ctx := e.Context()
opName := ʘBinOpNames[op.binOpType()]
name := fmt.Sprintf("%v.%v_ss_f%d", elemBinOpMod, opName, int(dt.Size())*8)
var mem, memB cu.DevicePtr
var size int64
if prealloc == nil {
mem = cu.DevicePtr(a.Uintptr())
retVal = a
size = int64(logicalSize(a.Shape()))
} else {
mem = cu.DevicePtr(prealloc.Uintptr())
memA := cu.DevicePtr(a.Uintptr())
memSize := int64(a.MemSize())
ctx.Memcpy(mem, memA, memSize)
size = int64(logicalSize(prealloc.Shape()))
retVal = prealloc
}
memB = cu.DevicePtr(b.Uintptr())
fn := e.Functions()[name]
var args []unsafe.Pointer
cudaLogf("%v mem %v, memB %v", op, mem, memB)
gridDimX, gridDimY, gridDimZ, blockDimX, blockDimY, blockDimZ := e.ElemGridSize(int(size))
args = []unsafe.Pointer{
unsafe.Pointer(&mem),
unsafe.Pointer(&memB),
unsafe.Pointer(&size),
}
cudaLogf("CUDADO %q, size %v", name, size)
cudaLogf("LaunchKernel params. mem: %v memB: %v size: %v", mem, memB, size)
cudaLogf("%d, %d, %d, %d, %d, %d", gridDimX, gridDimY, gridDimZ, blockDimX, blockDimY, blockDimZ)
ctx.LaunchAndSync(fn, gridDimX, gridDimY, gridDimZ, blockDimX, blockDimY, blockDimZ, 0, cu.NoStream, args)
return
}
/* LINEAR ALGEBRA STUFF */
func (op linAlgBinOp) CallsExtern() bool { return true }
func (op linAlgBinOp) CUDADo(extern External, dev Device, prealloc Value, inputs ...Value) (retVal Value, err error) {
if err = checkArity(op, len(inputs)); err != nil {
return
}
m := extern.(CUDAMachine)
e := &m.Engines()[int(dev)]
a := inputs[0]
b := inputs[1]
aT, ok := a.(tensor.Tensor)
if !ok {
return nil, errors.Errorf("Expected a a to be a Tensor. Got %T instead", a)
}
bT, ok := b.(tensor.Tensor)
if !ok {
return nil, errors.Errorf("Expected a b to be a Tensor. Got %T instead", b)
}
pT, ok := prealloc.(tensor.Tensor)
if !ok {
return nil, errors.Errorf("Expected a prealloc to be a Tensor. Got %T instead", prealloc)
}
tensor.WithEngine(e)(bT)
tensor.WithEngine(e)(aT)
tensor.WithEngine(e)(pT)
if op.transA && op.āBinaryOperator != batchedMatMulOperator {
if err = aT.T(); err != nil {
return nil, errors.Wrap(err, tFail)
}
// untranspose
defer aT.T()
}
if op.transB && op.āBinaryOperator != batchedMatMulOperator {
if err = bT.T(); err != nil {
return nil, errors.Wrap(err, tFail)
}
// untranspose
defer bT.T()
}
switch op.āBinaryOperator {
case matMulOperator:
return tensor.MatMul(aT, bT, tensor.WithReuse(pT))
case matVecMulOperator:
return tensor.MatVecMul(aT, bT, tensor.WithReuse(pT))
case vecDotOperator:
return nil, errors.New("NYI")
case outerProdOperator:
return tensor.Outer(aT, bT, tensor.WithReuse(pT))
case batchedMatMulOperator:
return nil, errors.New("NYI")
}
panic("Unreachable")
}
/* API stuff */
// NewAddOp creates a new *ExternalOp that wraps a add op
func NewAddOp(a, b *Node, ctx ExecutionContext) *ExternalOp {
add := newElemBinOp(addOpType, a, b)
op := NewExternalOp(add, ctx, nil)
if a.Device() == CPU && b.Device() == CPU {
op.Device = CPU
return op
}
if a.Device() != CPU {
op.Device = a.Device()
return op
}
if b.Device() != CPU {
op.Device = b.Device()
return op
}
return op
}
// NewSubOp creates a new *ExternalOp that wraps a sub op
func NewSubOp(a, b *Node, ctx ExecutionContext) *ExternalOp {
sub := newEBOByType(subOpType, a.t, b.t)
op := NewExternalOp(sub, ctx, nil)
if a.Device() == CPU && b.Device() == CPU {
op.Device = CPU
return op
}
if a.Device() != CPU {
op.Device = a.Device()
return op
}
if b.Device() != CPU {
op.Device = b.Device()
return op
}
return op
}
func NewHadamardProdOp(a, b *Node, ctx ExecutionContext) *ExternalOp {
mul := newEBOByType(mulOpType, a.t, b.t)
op := NewExternalOp(mul, ctx, nil)
if a.Device() == CPU && b.Device() == CPU {
op.Device = CPU
return op
}
if a.Device() != CPU {
op.Device = a.Device()
return op
}
if b.Device() != CPU {
op.Device = b.Device()
return op
}
return op
}