func main() {
nimble.Init()
defer nimble.Cleanup()
nimble.SetOD("demag1.out")
gpu.LockCudaThread()
N0, N1, N2 := 1, 3*64, 5*64
cx, cy, cz := 3e-9, 3.125e-9, 3.125e-9
mesh := nimble.NewMesh(N0, N1, N2, cx, cy, cz)
fmt.Println("mesh:", mesh)
mbox := gpu.NewConst("m", "", mesh, nimble.UnifiedMemory, []float64{1, 0, 0})
m := mbox.Output()
const acc = 4
kernel := mag.BruteKernel(mesh, acc)
conv := gpu.NewConvolution("B", "T", mesh, nimble.UnifiedMemory, kernel, m)
B := conv.Output()
const probe = 24 * 121
outputc := B.NewReader()
nimble.RunStack()
output := host(outputc.ReadNext(mesh.NCell()))
if output[0][probe] > -0.97 || output[0][probe] < -0.99 || output[1][probe] != 0 || output[2][probe] != 0 {
fmt.Println("failed, got:", output[0][probe])
os.Exit(2)
} else {
fmt.Println("OK")
}
}
// Precision test for the kernel: thin film.
func main() {
nimble.Init()
defer nimble.Cleanup()
nimble.SetOD("kernel-film.out")
gpu.LockCudaThread()
Y, X := core.IntArg(0), core.IntArg(1)
y, x := float64(Y), float64(X)
N0, N1, N2 := 1, 1024/Y, 1024/X
cx, cy, cz := 1e-9, 1e-9*y, 1e-9*x
mesh := nimble.NewMesh(N0, N1, N2, cx, cy, cz)
fmt.Println("mesh:", mesh)
mbox := gpu.NewConst("m", "", mesh, nimble.UnifiedMemory, []float64{1, 0, 0})
m := mbox.Output()
acc := 4.
kernel := mag.BruteKernel(mesh, acc)
conv := gpu.NewConvolution("B", "T", mesh, nimble.UnifiedMemory, kernel, m)
B := conv.Output()
outputc := B.NewReader()
nimble.RunStack()
output := host(outputc.ReadNext(mesh.NCell()))
Bz := core.Reshape(output[0], [3]int{N0, N1, N2})
probe := float64(Bz[N0/2][N1/2][N2/2])
fmt.Println(probe)
want := -1.
if math.Abs(probe-want) > 0.01 {
fmt.Println("FAIL")
os.Exit(2)
} else {
fmt.Println("OK")
}
}
func main() {
nimble.Init()
defer nimble.Cleanup()
nimble.SetOD("demag2.out")
gpu.LockCudaThread()
N0, N1, N2 := 4, 32, 1024
cx, cy, cz := 3e-9, 3.125e-9, 3.125e-9
mesh := nimble.NewMesh(N0, N1, N2, cx, cy, cz)
fmt.Println("mesh:", mesh)
mbox := gpu.NewConst("m", "", mesh, nimble.UnifiedMemory, []float64{1, 0, 0})
m := mbox.Output()
const acc = 4
kernel := mag.BruteKernel(mesh, acc)
conv := gpu.NewConvolution("B", "T", mesh, nimble.UnifiedMemory, kernel, m)
B := conv.Output()
outputc := B.NewReader()
nimble.RunStack()
output := host(outputc.ReadNext(mesh.NCell()))
out0 := core.Reshape(output[0], mesh.Size())
out1 := core.Reshape(output[1], mesh.Size())
out2 := core.Reshape(output[2], mesh.Size())
X, Y, Z := N0/2, N1/2, N2/2
if out0[X][Y][Z] < -0.95 || out0[X][Y][Z] > -0.90 || out1[X][Y][Z] > 0.001 || out2[X][Y][Z] > 0.001 {
fmt.Println("failed, got:", out0[X][Y][Z], out1[X][Y][Z], out2[X][Y][Z])
os.Exit(2)
} else {
fmt.Println("OK")
}
}
func main() {
nimble.Init()
defer nimble.Cleanup()
nimble.SetOD("gpueuler.out")
N0, N1, N2 := 1, 32, 128
cx, cy, cz := 3e-9, 3.125e-9, 3.125e-9
mesh := nimble.NewMesh(N0, N1, N2, cx, cy, cz)
fmt.Println("mesh:", mesh)
m := nimble.MakeChanN(3, "m", "", mesh, nimble.UnifiedMemory, 0)
fmt.Println("m:", m)
acc := 8
kernel := mag.BruteKernel(mesh, acc)
B := conv.NewSymm2D("B", "T", mesh, nimble.UnifiedMemory, kernel, m).Output()
const (
Bsat = 1.0053
aex = mag.Mu0 * 13e-12 / Bsat
α = 1
)
//exch := cpu.NewExchange6("Bex", "T", nimble.UnifiedMemory, m.NewReader(), aex)
exch := gpu.NewExchange6("Bex", m, aex)
nimble.Stack(exch)
Bex := exch.Output()
// heff := MakeChan3("Heff", "", mesh)
Beff := gpu.NewSum("Beff", B, Bex, Bsat, 1, nimble.UnifiedMemory).Output()
tBox := gpu.NewLLGTorque("torque", m, Beff, α)
nimble.Stack(tBox)
torque := tBox.Output()
const dt = 100e-15
solver := gpu.NewEuler(m, torque, mag.Gamma0, dt)
M := cpu.Host(m.ChanN().UnsafeData())
for i := range M[2] {
M[2][i] = 1
M[1][i] = 0.1
}
every := 100
nimble.Autosave(B, every)
nimble.Autosave(m, every)
nimble.Autosave(Bex, every)
nimble.Autosave(Beff, every)
nimble.Autosave(torque, every)
nimble.Autotable(m, every)
nimble.RunStack()
solver.Steps(100)
res := cpu.Host(m.ChanN().UnsafeData())
got := [3]float32{res[0][0], res[1][0], res[2][0]}
expect := [3]float32{-0.033120323, 0.20761484, 0.9776498}
solver.Steps(10000)
fmt.Println("result:", got)
if got != expect {
fmt.Println("expected:", expect)
os.Exit(2)
} else {
fmt.Println("OK")
}
}
func main() {
nimble.Init()
defer nimble.Cleanup()
nimble.SetOD("test4.out")
N0, N1, N2 := 1, 32, 128
cx, cy, cz := 3e-9, 3.125e-9, 3.125e-9
mesh := nimble.NewMesh(N0, N1, N2, cx, cy, cz)
fmt.Println("mesh:", mesh)
m := nimble.MakeChanN(3, "m", "", mesh, nimble.UnifiedMemory, 0)
fmt.Println("m:", m)
acc := 8
kernel := mag.BruteKernel(mesh, acc)
B := gpu.NewConvolution("B", "T", mesh, nimble.UnifiedMemory, kernel, m).Output()
const Bsat = 1.0053
const aex = mag.Mu0 * 13e-12 / Bsat
exch := cpu.NewExchange6("Bex", "T", nimble.UnifiedMemory, m.NewReader(), aex)
Bex := exch.Output()
Beff := cpu.NewSum("Beff", B, Bex, Bsat, 1, nimble.UnifiedMemory).Output()
const alpha = 1
tbox := cpu.NewLLGTorque("torque", m, Beff, alpha)
nimble.Stack(tbox)
torque := tbox.Output()
const dt = 100e-15
solver := cpu.NewEuler(m, torque.NewReader(), mag.Gamma0, dt)
M := cpu.Host(m.ChanN().UnsafeData())
for i := range M[2] {
M[2][i] = 1
M[1][i] = 0.1
}
every := 100
uni.Autosave(B, every, cpu.CPUDevice)
uni.Autosave(m, every, cpu.CPUDevice)
uni.Autosave(Bex, every, cpu.CPUDevice)
uni.Autosave(Beff, every, cpu.CPUDevice)
uni.Autosave(torque, every, cpu.CPUDevice)
uni.Autotable(m, every, cpu.CPUDevice)
nimble.RunStack()
solver.Steps(100)
res := cpu.Host(m.ChanN().UnsafeData())
got := [3]float32{res[0][0], res[1][0], res[2][0]}
expect := [3]float32{-0.03450077, 0.21015842, 0.9770585}
fmt.Println("result:", got)
if got != expect {
fmt.Println("expected:", expect)
os.Exit(2)
} else {
fmt.Println("OK")
}
}
