{ "cells": [ { "cell_type": "markdown", "id": "06b2b63f", "metadata": {}, "source": [ "# Speed Comparisions (VIP vs GRaTeR-JAX)" ] }, { "cell_type": "markdown", "id": "ecf13008", "metadata": {}, "source": [ "This notebook provides comparisons between previous `numpy`-based implementations of GRaTeR (namely [VIP, the Vortex Image Processing package](https://vip.readthedocs.io/en/latest/tutorials/05B_fm_disks.html)). See below for the performance takeaways from these tests." ] }, { "cell_type": "code", "execution_count": 1, "id": "af9e8260", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/home/mihirkondapalli/anaconda3/envs/package-env/lib/python3.12/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n", " from .autonotebook import tqdm as notebook_tqdm\n", "2025-12-29 00:55:29.356320: W external/xla/xla/service/gpu/nvptx_compiler.cc:930] The NVIDIA driver's CUDA version is 12.2 which is older than the PTX compiler version 12.9.86. Because the driver is older than the PTX compiler version, XLA is disabling parallel compilation, which may slow down compilation. You should update your NVIDIA driver or use the NVIDIA-provided CUDA forward compatibility packages.\n" ] } ], "source": [ "import numpy as np\n", "import matplotlib.pyplot as plt\n", "\n", "from vip_hci.fm.scattered_light_disk import ScatteredLightDisk as VIP_ScatteredLightDisk\n", "from vip_hci.var.filters import frame_filter_lowpass\n", "\n", "from grater_jax.optimization.optimize_framework import Optimizer\n", "from grater_jax.disk_model.SLD_ojax import ScatteredLightDisk as JAX_ScatteredLightDisk\n", "from grater_jax.disk_model.SLD_utils import (\n", " DustEllipticalDistribution2PowerLaws,\n", " HenyeyGreenstein_SPF,\n", ")\n", "from grater_jax.disk_model.objective_functions import Parameter_Index\n", "import jax\n", "import os\n", "\n", "os.environ['XLA_PYTHON_CLIENT_MEM_FRACTION'] = '0.50'\n", "jax.config.update(\"jax_enable_x64\", True)\n" ] }, { "cell_type": "markdown", "id": "47b94723", "metadata": {}, "source": [ "## Model Generation Benchmarks" ] }, { "cell_type": "code", "execution_count": 2, "id": "ddd0cc66", "metadata": {}, "outputs": [], "source": [ "density = {\n", " \"name\": \"2PowerLaws\",\n", " \"a\": 60.0,\n", " \"ksi0\": 1.0,\n", " \"gamma\": 2.0,\n", " \"beta\": 1.0,\n", " \"ain\": 5.0,\n", " \"aout\": -5.0,\n", " \"e\": 0.0,\n", " \"dens_at_r0\": 1.0,\n", "}\n", "phase = {\"name\": \"HG\", \"g\": 0.3, \"polar\": False}\n", "\n", "vip_disk = VIP_ScatteredLightDisk(\n", " nx=200,\n", " ny=200,\n", " distance=50.0,\n", " itilt=60.0,\n", " omega=0.0,\n", " pxInArcsec=0.01225,\n", " pa=0.0,\n", " density_dico=density,\n", " spf_dico=phase,\n", " xdo=0.0,\n", " ydo=0.0,\n", ")\n", "vip_img = vip_disk.compute_scattered_light(halfNbSlices=25)" ] }, { "cell_type": "code", "execution_count": 3, "id": "b59c7ffc", "metadata": {}, "outputs": [], "source": [ "# Define Optimizer inputs\n", "spf_params = HenyeyGreenstein_SPF.params.copy()\n", "spf_params[\"g\"] = 0.3\n", "\n", "disk_params = Parameter_Index.disk_params.copy()\n", "misc_params = Parameter_Index.misc_params.copy()\n", "\n", "disk_params.update(\n", " {\n", " \"sma\": 60.0,\n", " \"alpha_in\": 5.0,\n", " \"alpha_out\": -5.0,\n", " \"ksi0\": 1.0,\n", " \"gamma\": 2.0,\n", " \"beta\": 1.0,\n", " \"e\": 0.0,\n", " \"dens_at_r0\": 1.0,\n", " \"inclination\": 60.0,\n", " \"position_angle\": 0.0,\n", " \"omega\": 0.0,\n", " \"x_center\": 100.0,\n", " \"y_center\": 100.0,\n", " \"halfNbSlices\": 25,\n", " }\n", ")\n", "\n", "misc_params.update(\n", " {\n", " \"distance\": 50.0,\n", " \"pxInArcsec\": 0.01225,\n", " \"nx\": 200,\n", " \"ny\": 200,\n", " \"halfNbSlices\": 25,\n", " \"flux_scaling\": 1,\n", " }\n", ")\n", "\n", "optimizer = Optimizer(\n", " DiskModel=JAX_ScatteredLightDisk,\n", " DistrModel=DustEllipticalDistribution2PowerLaws,\n", " FuncModel=HenyeyGreenstein_SPF,\n", " PSFModel=None,\n", " disk_params=disk_params,\n", " spf_params=spf_params,\n", " psf_params=None,\n", " misc_params=misc_params,\n", ")" ] }, { "cell_type": "code", "execution_count": 4, "id": "91838393", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Log-likelihood: 11.269991291554023\n", "Mean residual: 4.1291199921774543e-13\n", "Max residual: 3.401922725454736e-12\n" ] } ], "source": [ "# Generate JAX model\n", "jax_img = optimizer.get_model()\n", "\n", "# Compute likelihood\n", "err_map = np.ones_like(vip_img) * np.nanstd(vip_img)\n", "ll = optimizer.log_likelihood(vip_img, err_map)\n", "print(\"Log-likelihood:\", ll)\n", "\n", "# Compare residuals\n", "residual = vip_img - jax_img\n", "mean_resid = np.mean(np.abs(residual))\n", "max_resid = np.max(np.abs(residual))\n", "print(\"Mean residual:\", mean_resid)\n", "print(\"Max residual:\", max_resid)" ] }, { "cell_type": "markdown", "id": "5946c10f", "metadata": {}, "source": [ "### GRaTeR-JAX vs VIP Models" ] }, { "cell_type": "code", "execution_count": 5, "id": "b077973f", "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Visualization\n", "vmin = min(vip_img.min(), jax_img.min())\n", "vmax = max(vip_img.max(), jax_img.max())\n", "\n", "fig, axes = plt.subplots(1, 3, figsize=(15, 5))\n", "im0 = axes[0].imshow(vip_img, cmap=\"inferno\", vmin=vmin, vmax=vmax)\n", "axes[0].set_title(\"VIP (PSF-applied)\")\n", "fig.colorbar(im0, ax=axes[0], fraction=0.046, pad=0.04)\n", "\n", "im1 = axes[1].imshow(jax_img, cmap=\"inferno\", vmin=vmin, vmax=vmax)\n", "axes[1].set_title(\"GRaTeR-JAX (Optimizer)\")\n", "fig.colorbar(im1, ax=axes[1], fraction=0.046, pad=0.04)\n", "\n", "im2 = axes[2].imshow(residual, cmap=\"seismic\", vmin=-max_resid, vmax=max_resid)\n", "axes[2].set_title(\"Residual\")\n", "fig.colorbar(im2, ax=axes[2], fraction=0.046, pad=0.04)\n", "\n", "plt.tight_layout()\n", "plt.show()" ] }, { "cell_type": "markdown", "id": "20c4bda5", "metadata": {}, "source": [ "### GRaTeR-JAX vs VIP Runtimes" ] }, { "cell_type": "code", "execution_count": 6, "id": "29acdb39", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "129 ms ± 118 μs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n", "2.66 ms ± 2.5 μs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n" ] } ], "source": [ "%timeit vip_disk.compute_scattered_light(halfNbSlices=25)\n", "%timeit optimizer.get_model()" ] }, { "cell_type": "markdown", "id": "4b86df39", "metadata": {}, "source": [ "## GRaTeR-JAX vs VIP Gradient Benchmarks" ] }, { "cell_type": "code", "execution_count": 7, "id": "b08f251f", "metadata": {}, "outputs": [], "source": [ "from vip_hci.fm.scattered_light_disk import ScatteredLightDisk as VIP_ScatteredLightDisk\n", "from grater_jax.optimization.optimize_framework import Optimizer, OptimizeUtils\n", "from grater_jax.disk_model.SLD_ojax import ScatteredLightDisk\n", "from grater_jax.disk_model.SLD_utils import (\n", " DustEllipticalDistribution2PowerLaws,\n", " InterpolatedUnivariateSpline_SPF,\n", " EMP_PSF,\n", ")\n", "from grater_jax.disk_model.objective_functions import Parameter_Index\n", "\n", "# Synthetic target\n", "def generate_vip_synthetic_target(nx=200, ny=200):\n", " density = {\n", " \"name\": \"2PowerLaws\",\n", " \"a\": 60.0,\n", " \"ksi0\": 1.0,\n", " \"gamma\": 2.0,\n", " \"beta\": 1.0,\n", " \"ain\": 5.0,\n", " \"aout\": -5.0,\n", " \"e\": 0.0,\n", " \"dens_at_r0\": 1.0,\n", " }\n", " phase = {\"name\": \"HG\", \"g\": 0.3, \"polar\": False}\n", "\n", " vip_disk = VIP_ScatteredLightDisk(\n", " nx=nx, ny=ny,\n", " distance=50.0,\n", " itilt=60.0,\n", " omega=0.0,\n", " pxInArcsec=0.01225,\n", " pa=0.0,\n", " density_dico=density,\n", " spf_dico=phase,\n", " xdo=0.0, ydo=0.0\n", " )\n", "\n", " vip_img = vip_disk.compute_scattered_light(halfNbSlices=25)\n", " return vip_img\n" ] }, { "cell_type": "code", "execution_count": 8, "id": "b0092846", "metadata": {}, "outputs": [], "source": [ "# Synthetic VIP target\n", "target_image = generate_vip_synthetic_target(nx=200, ny=200)\n", "err_map = np.ones_like(target_image, dtype=np.float32)\n", "\n", "# GRaTeR-JAX parameter setup\n", "start_disk_params = Parameter_Index.disk_params.copy()\n", "start_spf_params = InterpolatedUnivariateSpline_SPF.params.copy()\n", "\n", "# No PSF → both the class and params are None\n", "start_psf_params = None\n", "\n", "start_misc_params = Parameter_Index.misc_params.copy()\n", "\n", "start_disk_params.update({\n", " \"sma\": 46.0,\n", " \"inclination\": 80.0,\n", " \"position_angle\": 27.5,\n", " \"x_center\": 100.0,\n", " \"y_center\": 100.0,\n", " \"flux_scaling\": 1.0,\n", "})\n", "\n", "start_spf_params[\"num_knots\"] = 5\n", "start_spf_params[\"knot_values\"] = np.ones(5) * 0.5\n", "\n", "start_misc_params.update({\n", " \"distance\": 50.0,\n", " \"nx\": 200,\n", " \"ny\": 200,\n", " \"pxInArcsec\": 0.01225,\n", "})\n", "\n", "# Initialize optimizer with NO PSF model\n", "opt = Optimizer(\n", " ScatteredLightDisk,\n", " DustEllipticalDistribution2PowerLaws,\n", " InterpolatedUnivariateSpline_SPF,\n", " PSFModel=None,\n", " disk_params=start_disk_params,\n", " spf_params=start_spf_params,\n", " psf_params=start_psf_params,\n", " misc_params=start_misc_params,\n", ")\n", "\n", "# SPF knots\n", "opt.inc_bound_knots()\n", "opt.initialize_knots(target_image)\n", "\n", "# Compile model + gradient (no PSF path)\n", "opt.jit_compile_model()\n", "opt.jit_compile_gradient(target_image, err_map)" ] }, { "cell_type": "code", "execution_count": 9, "id": "2ffc7da9", "metadata": {}, "outputs": [], "source": [ "from grater_jax.disk_model.objective_functions import log_likelihood" ] }, { "cell_type": "code", "execution_count": 10, "id": "716f8f6b", "metadata": {}, "outputs": [], "source": [ "fit_keys = [\"sma\", \"alpha_in\", \"inclination\", \"position_angle\", \"x_center\", \"y_center\", \"alpha_out\", \"knot_values\"]\n", "\n", "def analytic_grad():\n", " return opt.get_gradient(fit_keys, target_image, err_map)\n", "\n", "def numeric_grad(eps=1e-6):\n", " \"\"\"\n", " Finite-difference numerical gradient for the current optimizer state.\n", " Supports both scalar parameters and vector-valued knot_values.\n", " \"\"\"\n", "\n", " base_params = opt.get_values(keys=fit_keys)\n", " grad = []\n", "\n", " for k in range(len(fit_keys)):\n", " val = base_params[k]\n", "\n", " if np.isscalar(val):\n", " params_plus = base_params.copy()\n", " params_minus = base_params.copy()\n", "\n", " params_plus[k] = val + eps\n", " params_minus[k] = val - eps\n", "\n", " ll_plus = opt.get_objective_likelihood(\n", " params_plus, fit_keys, target_image, err_map\n", " )\n", " ll_minus = opt.get_objective_likelihood(\n", " params_minus, fit_keys, target_image, err_map\n", " )\n", "\n", " grad.append((ll_plus - ll_minus) / (2 * eps))\n", " else:\n", " g = np.zeros_like(val)\n", " for i in range(len(val)):\n", " params_plus = base_params.copy()\n", " params_minus = base_params.copy()\n", " v_plus = val.at[i].set(val[i] + eps)\n", " v_minus = val.at[i].set(val[i] - eps)\n", " params_plus[k] = v_plus\n", " params_minus[k] = v_minus\n", " ll_plus = opt.get_objective_likelihood(\n", " params_plus, fit_keys, target_image, err_map\n", " )\n", " ll_minus = opt.get_objective_likelihood(\n", " params_minus, fit_keys, target_image, err_map\n", " )\n", " g[i] = (ll_plus - ll_minus) / (2 * eps)\n", " grad.append(g)\n", "\n", " return grad\n" ] }, { "cell_type": "code", "execution_count": 11, "id": "ecf8e0ca", "metadata": {}, "outputs": [], "source": [ "def make_vip_disk(params_dict):\n", " density = {\n", " \"name\": \"2PowerLaws\",\n", " \"a\": params_dict[\"sma\"],\n", " \"ksi0\": 1.0,\n", " \"gamma\": 2.0,\n", " \"beta\": 1.0,\n", " \"ain\": params_dict[\"alpha_in\"],\n", " \"aout\": params_dict[\"alpha_out\"],\n", " \"e\": 0.0,\n", " \"dens_at_r0\": 1.0,\n", " }\n", "\n", " phase = {\n", " \"name\": \"HG\",\n", " \"g\": params_dict[\"g\"],\n", " \"polar\": False, }\n", "\n", " return VIP_ScatteredLightDisk(\n", " nx=200,\n", " ny=200,\n", " distance=50.0,\n", " itilt=params_dict[\"inclination\"],\n", " omega=0.0,\n", " pxInArcsec=0.01225,\n", " pa=params_dict[\"position_angle\"],\n", " density_dico=density,\n", " spf_dico=phase,\n", " xdo=100-params_dict[\"x_center\"],\n", " ydo=100-params_dict[\"y_center\"]\n", " )\n", "\n", "vip_fit_keys = [\"sma\", \"alpha_in\", \"inclination\", \"position_angle\", \"x_center\", \"y_center\", \"alpha_out\", \"g\"]\n", "vip_fit_values = [46.0, 5.0, 80.0, 27.5, 100.0, 100.0, -5.0, 0.3]\n", "base_dict = dict(zip(vip_fit_keys, vip_fit_values))\n", "\n", "def numeric_grad_vip(eps=1e-6):\n", " \"\"\"\n", " Finite-difference numerical gradient using VIP scattered-light images.\n", " \"\"\"\n", " grad = []\n", "\n", " for k, key in enumerate(vip_fit_keys):\n", " val = vip_fit_values[k]\n", "\n", " if np.isscalar(val):\n", " dict_plus = dict(base_dict)\n", " dict_minus = dict(base_dict)\n", " dict_plus[key] = val + eps\n", " dict_minus[key] = val - eps\n", "\n", " img_plus = make_vip_disk(dict_plus).compute_scattered_light(halfNbSlices=25)\n", " img_minus = make_vip_disk(dict_minus).compute_scattered_light(halfNbSlices=25)\n", "\n", " ll_plus = log_likelihood(img_plus, target_image, err_map)\n", " ll_minus = log_likelihood(img_minus, target_image, err_map)\n", "\n", " grad.append((ll_plus - ll_minus) / (2 * eps))\n", "\n", " return grad\n" ] }, { "cell_type": "markdown", "id": "752f227d", "metadata": {}, "source": [ "### Numeric vs Analytic Gradients\n", "\n", "VIP does not have the capability to generate numeric gradients, so I will isolate the performance improvement of GRaTeR-JAX's analyitic gradient function by comparing the analyitic gradient with a numeric function for a GRaTeR-JAX objective function." ] }, { "cell_type": "code", "execution_count": 12, "id": "f820e7c8", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Analytic Gradient: [1.41e-12, 3.40e-12, -2.45e-12, 3.56e-13, 3.42e-13, -1.06e-13, 1.01e-14, -3.40e-12, -2.38e-13, 2.01e-12, 1.56e-12, 1.38e-13]\n", "Numeric Gradient: [1.41e-12, 3.40e-12, -2.45e-12, 3.56e-13, 8.22e-13, 2.30e-14, 1.01e-14, -3.40e-12, -2.38e-13, 2.01e-12, 1.56e-12, 1.38e-13]\n" ] } ], "source": [ "def compress_grad(grad_list):\n", " out = []\n", " for g in grad_list:\n", " if np.isscalar(g):\n", " out.append(float(g))\n", " else:\n", " out.extend(np.asarray(g).ravel().astype(float).tolist())\n", " return out\n", "\n", "def format_list(vals, ndigits=2):\n", " return \"[\" + \", \".join(f\"{v:.{ndigits}e}\" for v in vals) + \"]\"\n", "\n", "print(\"Analytic Gradient:\", format_list(compress_grad(analytic_grad()), 2))\n", "print(\"Numeric Gradient:\", format_list(compress_grad(numeric_grad()), 2))\n" ] }, { "cell_type": "markdown", "id": "4388aeca", "metadata": {}, "source": [ "### VIP (numeric) vs GRaTeR-JAX Gradient Runtimes" ] }, { "cell_type": "code", "execution_count": 14, "id": "69d3f260", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "159 ms ± 614 μs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n", "29 ms ± 28.9 μs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n", "2.08 s ± 9.76 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)\n" ] } ], "source": [ "%timeit numeric_grad()\n", "%timeit analytic_grad()\n", "%timeit numeric_grad_vip()" ] }, { "cell_type": "markdown", "id": "f440f9e7", "metadata": {}, "source": [ "# Performance Takeaways\n", "\n", "GRaTeR-JAX delivers substantial performance improvements over the legacy VIP GRaTeR disk framework in both **model generation** and **gradient evaluation**. These gains are enabled by JAX-based vectorization, XLA compilation, and analytic differentiation, making GRaTeR-JAX significantly more scalable for optimization and inference workflows.\n", "\n", "---\n", "\n", "## Benchmark Summary\n", "\n", "| Task | Framework | Method | Runtime per Loop | Speedup |\n", "|-----:|-----------|--------|------------------|---------|\n", "| Model generation | VIP GRaTeR | Native | 104 ms ± 99.9 μs | 1× |\n", "| Model generation | GRaTeR-JAX | JAX model | 2.67 ms ± 1.97 μs | **~39×** |\n", "| Gradient | VIP GRaTeR | Numeric (FD) | 1.71 s ± 4.06 ms | 1× |\n", "| Gradient | GRaTeR-JAX | Numeric (FD) | 159 ms ± 777 μs | ~11× |\n", "| Gradient | GRaTeR-JAX | Analytic (AD) | 29.1 ms ± 17.6 μs | **~59×** |\n", "\n", "---\n", "\n", "## Model Generation Performance\n", "\n", "We compare scattered-light model generation between:\n", "\n", "- **VIP GRaTeR**: `vip_disk.compute_scattered_light`\n", "- **GRaTeR-JAX**: `optimizer.get_model`\n", "\n", "```python\n", "%timeit vip_disk.compute_scattered_light(halfNbSlices=25)\n", "%timeit optimizer.get_model()\n", "```\n", "\n", "**Results**\n", "\n", "- VIP GRaTeR \n", " 104 ms ± 99.9 μs per loop \n", " (mean ± std. dev. of 7 runs, 10 loops each)\n", "\n", "- GRaTeR-JAX \n", " 2.67 ms ± 1.97 μs per loop \n", " (mean ± std. dev. of 7 runs, 100 loops each)\n", "\n", "**Speedup**\n", "\n", "GRaTeR-JAX achieves a **~39× reduction** in model generation runtime.\n", "\n", "This improvement dramatically reduces the cost of iterative workflows such as gradient-based fitting, MCMC sampling, and large-scale parameter sweeps.\n", "\n", "---\n", "\n", "## Gradient Computation Performance\n", "\n", "Three gradient computation scenarios are evaluated:\n", "\n", "```python\n", "%timeit numeric_grad()\n", "%timeit analytic_grad()\n", "%timeit numeric_grad_vip()\n", "```\n", "\n", "**Results**\n", "\n", "- GRaTeR-JAX numeric gradient \n", " 159 ms ± 777 μs per loop \n", " (7 runs, 10 loops each)\n", "\n", "- GRaTeR-JAX analytic gradient \n", " 29.1 ms ± 17.6 μs per loop \n", " (7 runs, 10 loops each)\n", "\n", "- VIP numeric gradient \n", " 1.71 s ± 4.06 ms per loop \n", " (7 runs, 1 loop each)\n", "\n", "### Notes on Comparability\n", "\n", "- The **numeric and analytic gradients** are computed on the **same GRaTeR-JAX model**, allowing for a direct comparison (12 parameters).\n", "- The **VIP numeric gradient** corresponds to a different model configuration (8 parameters), as VIP does **not support spline-based SPF functions**. It is included as a realistic reference for legacy workflows rather than a strict apples-to-apples comparison.\n", "\n", "---\n", "\n", "## Gradient Speedups\n", "\n", "- **Analytic vs numeric (GRaTeR-JAX)** \n", " → **~5.6× speedup** for a 12-parameter fit\n", "\n", "- **Analytic GRaTeR-JAX vs numeric VIP** \n", " → **~59× speedup** in gradient evaluation\n", "\n", "In addition to performance gains, analytic gradients eliminate numerical instability and poor scaling behavior inherent to finite-difference methods.\n", "\n", "---\n", "\n", "## Summary\n", "\n", "- Model generation is nearly **40× faster** with GRaTeR-JAX.\n", "- Analytic gradients provide:\n", " - Significant runtime reductions\n", " - Improved numerical stability\n", " - Better scaling with parameter dimensionality\n", "- GRaTeR-JAX enables workflows that are impractical with VIP, including high-dimensional optimization, HMC/NUTS sampling, and interactive modeling.\n", "\n", "Overall, GRaTeR-JAX represents a substantial advance in both **performance** and **scalability** for scattered-light disk modeling.\n" ] } ], "metadata": { "kernelspec": { "display_name": "package-env", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.12.12" } }, "nbformat": 4, "nbformat_minor": 5 }