# Slow ec2 comparing to my mac m2 machine
**URL:** https://discourse.vtk.org/t/slow-ec2-comparing-to-my-mac-m2-machine/14979
**Category:** Support
**Tags:** python
**Created:** [December 8, 2024, 12:02pm UTC](https://discourse.vtk.org/t/slow-ec2-comparing-to-my-mac-m2-machine/14979 "2024-12-08T12:02:31Z")
**Posts on this page:** 3
**Page:** 1
### Author:  [@DanielAmmar](https://discourse.vtk.org/u/DanielAmmar)
#### Post date: [December 8, 2024, 12:02pm UTC](https://discourse.vtk.org/t/slow-ec2-comparing-to-my-mac-m2-machine/14979/1 "2024-12-08T12:02:31Z")
Hello,
I found that my mac m2 is much faster performing the following code, comparing to bigger machines in the cloud (c7i.8xlarge, g5.2xlarge), and I suspect this is something to do with connecting to the screen.
```auto
Class MyRenderer:
def __init__ (self, mesh: trimesh.Trimesh):
self.vtkmesh = create_vtk_mesh(mesh.vertices, mesh.faces) # This returns vtkPolyData mesh
self.renderer = vtk.vtkRenderer()
self.render_window = vtk.vtkRenderWindow()
self.render_window.AddRenderer(self.renderer)
self.render_window.SetOffScreenRendering(False)
self.render_window.SetSize(128, 128)
mapper = vtk.vtkPolyDataMapper()
mapper.SetInputData(self.vtkmesh)
actor = vtk.vtkActor()
actor.SetMapper(mapper)
self.renderer.AddActor(actor)
self.camera = vtk.vtkCamera()
self.camera.ParallelProjectionOn()
self.camera.SetParallelScale(75)
self.camera.SetClippingRange(1, 400)
self.renderer.SetActiveCamera(self.camera)
self.render_window.Render()
def render_mesh(self, camera_position: np.ndarray, camera_focal_point: np.ndarray, pts_3d=None):
self.camera.SetPosition(*camera_position)
self.camera.SetFocalPoint(*camera_focal_point)
view_matrix = self.camera.GetViewTransformMatrix()
projection_matrix = self.camera.GetProjectionTransformMatrix(1, -1, 1)
view_matrix_np = np.array([view_matrix.GetElement(i, j) for i in range(4) for j in range(4)]).reshape((4, 4))
projection_matrix_np = np.array([projection_matrix.GetElement(i, j) for i in range(4) for j in range(4)]).reshape((4, 4))
rotation_det = np.linalg.det(view_matrix_np[:3, :3])
imaging_matrix = projection_matrix_np @ view_matrix_np
sensor_normal = camera_focal_point - camera_position
sensor_normal = sensor_normal / np.linalg.norm(sensor_normal)
sensor_plane = sensor_normal[0], sensor_normal[1], sensor_normal[2], -np.dot(camera_position, sensor_normal)
self.renderer.SetActiveCamera(self.camera)
self.render_window.Render()
window_to_image_filter = vtk.vtkWindowToImageFilter()
window_to_image_filter.SetInput(self.render_window)
# Bencmark:
# On Apple MAC M2 - 0.001
# AWS EC2 c7i.8xlarge Amazon linux (cpu) - 0.130
# AWS EC2 g5.2xlarge Ubuntu (GPU) - 0.134
with timing('this is slow'):
window_to_image_filter.Update()
```
Calling `window_to_image_filter.Update()` on my laptop takes approximately 0.001 seconds, while doing the same on the machine in the cloud is 100 slower.
I’m using xvfb, and also try to run it with vtk-osmesa instead of vtk-9.4.0.
How can I make it as fast as my laptop? or at least 10x faster?
---
### Author:  [@Sebastien\_Jourdain](https://discourse.vtk.org/u/Sebastien_Jourdain)
#### Post date: [December 9, 2024, 4:42pm UTC](https://discourse.vtk.org/t/slow-ec2-comparing-to-my-mac-m2-machine/14979/2 "2024-12-09T16:42:30Z")
The reason why it is slow, is because OSMesa get picked up for doing the rendering.
If you have graphic hardware (`g5.*`), you should be able to use EGL which is embedded in 9.4 but would require you to have the nvidia drivers properly installed on that machine.
---
### Author:  [@whereismymoney](https://discourse.vtk.org/u/whereismymoney)
#### Post date: [December 10, 2024, 5:49am UTC](https://discourse.vtk.org/t/slow-ec2-comparing-to-my-mac-m2-machine/14979/3 "2024-12-10T05:49:25Z")
We have had great performance with Nice DCV for Amazon Linux 2.
We use the g4 series, which are GPU(graphics) enabled. g4dn=nvidia g4ad=AMD