Beispiel #1
0
// 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")
	}
}
Beispiel #2
0
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")
	}
}
Beispiel #3
0
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")
	}
}
Beispiel #4
0
func Live(in_ nimble.ChanN) {
	go func() {
		in := in_.NewReader()

		Frame = new(dump.Frame)
		Frame.Components = in.NComp()
		Frame.MeshSize = in.Mesh().Size()
		Frame.MeshStep = in.Mesh().CellSize()
		Crop2 = Frame.MeshSize
		ncell := in.Mesh().NCell()
		n := ncell * in.NComp()
		Frame.Data = make([]float32, n)

		Init(800, 600, true, 2, true)
		InitInputHandlers()
		defer glfw.CloseWindow()
		defer glfw.Terminate()
		Viewpos[2] = -20

		wantframe := new(atomicbool)
		wantframe.set(true)

		go func() {
			gpu.LockCudaThread()
			for {
				data := in.ReadNext(ncell)
				if wantframe.get() {
					for i, d := range data {
						d.Device().CopyDtoH(Frame.Data[i*ncell : (i+1)*ncell])
					}
					wantframe.set(false)
				}
				in.ReadDone()
			}
		}()

		for glfw.WindowParam(glfw.Opened) == 1 { // window open
			Render()
			if Wantscrot {
				Screenshot()
				Wantscrot = false
			}
			if wantframe.get() == false {
				PreRender(Frame)
				wantframe.set(true)
			}
		}
	}()
}
Beispiel #5
0
// Standard problem 4 on GPU
func main() {
	nimble.Init()
	defer nimble.Cleanup()
	nimble.SetOD("gpu4-3d.out")
	gpu.LockCudaThread()

	mem := nimble.GPUMemory

	const (
		N0, N1, N2 = 1 * 2, 32, 128
		Sx, Sy, Sz = 3e-9, 125e-9, 500e-9
		cx, cy, cz = Sx / N0, Sy / N1, Sz / N2
		Bsat       = 800e3 * mag.Mu0
		Aex_red    = 13e-12 / (Bsat / mag.Mu0)
		α          = 1
	)

	mesh := nimble.NewMesh(N0, N1, N2, cx, cy, cz)
	fmt.Println("mesh:", mesh)

	// TODO: MakeChanN -> NewQuant()
	m := nimble.MakeChanN(3, "m", "", mesh, mem, 0)
	M := gpu.Device3(m.ChanN().UnsafeData())
	M[0].Memset(float32(1 / math.Sqrt(3)))
	M[1].Memset(float32(1 / math.Sqrt(3)))
	M[2].Memset(float32(1 / math.Sqrt(3)))

	acc := 5.
	kernel := mag.BruteKernel(mesh, acc)
	B := gpu.NewConvolution("B", "T", mesh, mem, kernel, m).Output()

	exch := gpu.NewExchange6("Bex", m, Aex_red)
	Bex := exch.Output()

	BeffBox := gpu.NewSum("Beff", B, Bex, Bsat, 1, mem)
	Beff := BeffBox.Output()

	tBox := gpu.NewLLGTorque("torque", m, Beff, α)
	torque := tBox.Output()

	solver := gpu.NewHeun(m, torque, 10e-15, mag.Gamma0)
	solver.Maxerr = 5e-4
	solver.Maxdt = 1e-12
	solver.Mindt = 1e-15
	solver.Headroom = 0.5

	every := 100
	uni.Autosave(m, every, gpu.GPUDevice)
	uni.Autotable(m, every/10, gpu.GPUDevice)

	solver.Advance(2e-9)

	var avg [3]float32
	for i := range avg {
		avg[i] = gpu.Sum(m.UnsafeData()[i].Device()) / float32(mesh.NCell())
	}
	want := [3]float32{0, 0.12521397, 0.9669811}
	err := math.Sqrt(float64(sqr(avg[0]-want[0]) + sqr(avg[1]-want[1]) + sqr(avg[2]-want[2])))
	fmt.Println("avg:", avg, "err:", err)
	if err > 1e-2 {
		fmt.Println("FAILED")
		os.Exit(2)
	}
	fmt.Println("OK")

	const (
		Bx = -24.6E-3
		By = 4.3E-3
		Bz = 0
	)
	Bext := gpu.NewConst("Bext", "T", mesh, mem, []float64{Bz, By, Bx}).Output()
	BeffBox.MAdd(Bext, 1)
	tBox.Alpha = 0.02
	solver.Advance(1e-9)

	for i := range avg {
		avg[i] = gpu.Sum(m.UnsafeData()[i].Device()) / float32(mesh.NCell())
	}

	want = [3]float32{0.04303933, 0.13000599, -0.9842051}
	err = math.Sqrt(float64(sqr(avg[0]-want[0]) + sqr(avg[1]-want[1]) + sqr(avg[2]-want[2])))
	fmt.Println("avg:", avg, "err:", err)
	if err > 1e-2 {
		fmt.Println("FAILED")
		os.Exit(2)
	}
	fmt.Println("OK")
}