I'm raymarching Signed Distance Fields in CUDA and the scene I'm rendering contains thousands of spheres (spheres have their location stored in device buffer, so my SDF function iterates through all of the spheres for each pixel).
Currently, I'm computing distance to sphere surface as:
sqrtf( dot( pos - sphere_center, pos - sphere_center ) ) - sphere_radius
With the sqrt() function, the rendering took about 250ms for my scene. However, when I removed the call to sqrt() and left just dot( pos - sphere_center, pos - sphere_center ) - sphere_radius, the rendering time dropped to 17ms (and rendering black image).
The sqrt() function seems to be the bottleneck so I want to ask if there is a way I can improve my rendering time (either by using different formula that does not use square root or different rendering approach)?
I'm already using -use-fast-math.
Edit: I've tried formula suggested by Nico Schertler, but it didn't work in my renderer. Link to M(n)WE on Shadertoy.
(Making my comment into an answer since it seems to have worked for OP)
You're feeling the pain of having to compute sqrt(). I sympathize... It would be great if you could just, umm, not do that. Well, what's stopping you? After all, the square-distance to a sphere is a monotone function from $R^+$ to $R^+$ - hell, it's actually a convex bijection! The problem is that you have non-squared distances coming from elsewhere, and you compute:
min(sqrt(square_distance_to_the_closest_sphere),
distance_to_the_closest_object_in_the_rest_of_the_scene)
So let's just do things the other way around: Instead of taking the square-root of the squared distance to the sphere, let's square the other distance:
min(square_distance_to_the_closest_sphere,
distance_to_the_closest_object_in_the_rest_of_the_scene^2)
This makes the same choice as the un-squared min() computation, due to the monotonicity of the squaring function. From here, try to propagate the use of the squared distance further in your program, avoiding taking a root as far as possible, perhaps even all the way.
Related
I am trying to write a Minecraft Datapack, which will plot a full armorstand circle around whatever runs the particular command. I am using a 3rd party mathematics datapack to use Sin and Cos. However, when running the command, the resulting plot was... not good. As you can see here: 1. Broken Circle., rather than have each vertex evenly placed in a circular line, I find a strange mess instead.
I would have thought loosing precision in Cos and Sin would simply make the circle more angular, I didn't expect it to spiral. What confuses me, is that +z (the red square) and -x (the purple one) are all alone. You can see on the blue ring (Which was made with a smaller radius) the gap between them persists.
My main issue is; How did my maths go from making a circle to a shredded mushroom, and is there a way to calculate the vertices with a greater precision?
Going into the project I knew I could simply spin the centre entity, and summon an armorstand x blocks in front using ^5 ^ ^, however I wanted to avoid this, due to my desire to be able to change the radius without needing to edit the datapack. To solve this, I used the Sin and Cos components to plot a new point, using a radius defined with scoreboards.
I first tested this using Scratch, in order to check my maths. You can see my code here: 2. Scratch code.
With an addition of the pen blocks, I was able to produce a perfect circle, which you can see here:
. Scratch visual proof.
With my proof of concept working, I looked online and found a Mathematical Functions datapack by yosho27, since the Cos and Sin functions are not built into the game. However, due to how Minecraft scoreboards are only Integers, Yosho27 multiplied the result of Cos and Sin by 100 to preserve 2 decimal places.
To start with, I am using a central armorstand with the tag center, which is at x: 8.5 z: 8.5. The scoreboards built into yosho's datapack that I am using is math_in for the values I want converted and math_out, which is where the final value is dumped.
Using signs, I keep track of the important values I am working with, as seen here: 4. Sign maths.
As I was writing this, I decided to actually compare both numbers to find this: 5. Image comparison, which shows me that somewhere in this calculation process, the maths has gone wrong. I modified the scratch side to match the minecraft conditions as much as possible, such as x100 and adding 850 to the result. From this result, I can see a disparity between x and z, even though they should be equal. Where Minecraft says 1: x= 864 z= 1487, Scratch says 1: x= 862.21668448: z= 1549.89338664. I assume this means the datapack's Cos and Sin are not accurate enough?
In light of this , I looked in yosho's datapack, I found this: 6. Yosho's code., which I just modified to be *= 10 instead of divide, in the hope of getting more precision. Modifying the rest of my code to match, I couldn't see any improvement in the numbers, although the armorstand vertices were a few pixels off the original circle, although I couldn't find a discernible pattern to this shift.
While this doesn't answer your full question, I'd like to point out two different ways you can solve the original issue at hand, no need to rely on some foreign math library:
^ ^ ^
Use Math, but let the game do it for you.
You can use the fact that the game is doing those rotational conversions for you already when using local coordinates. So, if you (or any entity) go to 0 0 0 and look / rotate in the angle that you want to calculate, then move forward by ^ ^ ^1, the position you're at now is basically <sin> 0 <cos>.
You can now take those numbers with your desired precision using data get and continue using them in whatever way you see fit.
Use recursive functions to move in incremenets
You point out in your question that
Going into the project I knew I could simply spin the centre entity, and summon an armorstand x blocks in front using ^5 ^ ^, however I wanted to avoid this, due to my desire to be able to change the radius without needing to edit the datapack. To solve this, I used the Sin and Cos components to plot a new point, using a radius defined with scoreboards.
So, to go back to that original idea, you could fairly easily (at least easier than trying to calculate the SIN/COS manually) find a solution that works for (almost) arbitrary radii and steps: By making the datapack configurable through e.g. scores, you can set it up to for example move forward by ^^^0.1 blocks for every point in a score, that way you can change that score to 50 to get a distance of ^^^5 and to 15 to get a distance of ^^^1.5.
Similarly you could set the "minimum" rotation between summons to be 0.1 degrees, then repeating said rotation for however many times you desire.
Both of these things can be achieved with recursive functions. Here is a quick example where you can control the rotational angle using the #rot steps score and the distance using the #dist steps score as described above (you might want to limit how often this runs with a score, too, like 360/rotation or whatever if you want to do one full circle). This example technically recurses twice, as I'm not using an entity to store the rotation. If there is an entity, you don't need to call the forward function from the rotate function but can call it from step (at the entity).
step.mcfunction
# copy scores over so we can use them
scoreboard players operation #rot_steps steps = #rot steps
scoreboard players operation #dist_steps steps = #dist steps
execute rotated ~ ~0.1 function foo:rotate
rotate.mcfunction
scoreboard players remove #rot_steps steps 1
execute if score #rot_steps matches ..0 positioned ^ ^ ^.1 run function foo:forward
execute if score #rot_steps matches 1.. rotated ~ ~0.1 run function foo:rotate
forward.mcfunction
scoreboard players remove #dist_steps steps 1
execute if score #dist_steps matches ..0 run summon armor_stand
execute if score #dist_steps matches 1.. positioned ^ ^ ^.1 run function foo:forward
I have a 3D point in space, and I need to know how to pitch/yaw/roll my current heading (in the form of a 3d unit vector) to face a point. I am familiar with quaternions and rotation matrices, and I know how to represent the total rotation necessary to get my desired answer.
However, I only have control over pitch, yaw, and roll velocities (I can 'instantaneously' set their respective angular velocities), and only occasional updates on my new orientation (once every second or so). The end goal is to have some sort of PID controller (or three separates ones, but I suspect it won't work like that) controlling my current orientation. the end effect would be a slow (and hopefully convergent) wobble towards a steady state in the direction of my destination.
I have no idea how to convert the current desired quaternion/rotation matrix into a set of pitch-yaw-roll angular velocities (some sort of quaternion derivative or something?). I'm not even sure what to search for. I'm also uncertain how to apply a PID controller to this system, because I suspect there will need to be one controller for the trio as opposed to treating them each independently (although intuitively I feel this should be possible). Can anyone offer any guidance?
As a side note, if there is a solution that just involves a duo (pitch/yaw, roll/pitch, etc), then that works just fine too. I should only need 2 rotational degrees of freedom for this, but that is further from a realm that I am familiar with so I was less confident forming the question around it.
First take a look if your problem can be solved using quaternion SLERP [1], which can let you specify a scalar between 0 and 1 as the control to move from q1-->q2.
If you still need to control using the angular rotations then you can calculate the error quaternion as Nico Schertler suggested.
From that error quaternion you can use the derivative property of the quaternion (Section 4 of http://www.ecsutton.ece.ufl.edu/ens/handouts/quaternions.pdf [2]) to work out the angular rates required.
I'm pretty sure that will work, but if it does not you can also look at using the SLERP derivative (eq. 23 of http://www.geometrictools.com/Documentation/Quaternions.pdf [3]) and equating that to the Right-Hand-Side of the equation in source [2] to again get angular rates. The disadvantage to this is that you need code implementations for the quaternion exponentiation and logarithm operations.
I am quite new to this, and iv'e heard that i need to get my inversed projection matrix and so on to create a ray from a 2D point to a 3D world point, however since im using OpenglES and there are not as many methods as there would be regulary to help me with this. (And i simply don't know how to do it) im using a trigenomeric formula for this insted.
For each time i iterate one step down the negative Z-axis i multiply the Y-position on the screen (-1 to 1) with
(-z / (cot(myAngle / 2))
And the X position likewise but with a koefficent equally to the aspect ratio.
myAngle is the frustum perspective angle.
This works really good for me and i get very accurate values, so what i wonder is: Why should i use the inverse of the projection matrix and multiply it with some stuff instead of using this?
Most of the time you have a matrix lying around for your OpenGl camera. Using an inverse matrix is simple when you already have a camera matrix on hand. It is also (oh so very slightly at computer speeds) faster to do a matrix multiply. And in cases where you are doing a bajillion of these calculations per frame, it can matter.
Here is some good info on getting started on a camera class if you are interested:
Camera Class
And some matrix resources
Depending on what you are working on, I wouldn't worry too much about the 'best way to do it.' You just want to make sure you understand what your code is doing then keep improving it.
I'm working on a 2D physics engine for a game. I have gravity and masses working, using a simple iterative approach (that I know I'll have to upgrade eventually); I can push the masses around manually and watch them move and it all works as I'd expect.
Right now I'm trying to set up the game world in advance with a satellite in a simple circular orbit around a planet. To do this I need to calculate the initial velocity vector of the satellite given the mass of the planet and the desired distance out; this should be trivial, but I cannot for the life of me get it working right.
Standard physics textbooks tell me that the orbital velocity of an object in circular orbit around a mass M is:
v = sqrt( G * M / r )
However, after applying the appropriate vector the satellite isn't going anything like fast enough and falls in in a sharply elliptical orbit. Random tinkering shows that it's off by about a factor of 3 in one case.
My gravity simulation code is using the traditional:
F = G M m / r^2
G is set to 1 in my universe.
Can someone confirm to me that these equations do still hold in 2D space? I can't see any reason why not, but at this point I really want to know whether the problem is in my code or my assumptions...
Update: My physics engine works as follows:
for each time step of length t:
reset cumulative forces on each object to 0.
for each unique pair of objects:
calculate force between them due to gravity.
accumulate force to the two objects.
for each object:
calculate velocity change dV for this timestep using Ft / m.
v = v + dV.
calculate position change dS using v * t.
s = s + dS.
(Using vectors where appropriate, of course.)
Right now I'm doing one physics tick every frame, which is happening about 500-700 times per second. I'm aware that this will accumulate errors very quickly, but it should at least get me started.
(BTW, I was unable to find an off-the-shelf physics engine that handles orbital mechanics --- most 2D physics engines like Chipmunk and Box2D are more focused on rigid structures instead. Can anyone suggest one I could look at?)
You need to make sure that your delta t iterative time value is small enough. You will definitely have to tinker with the constants in order to get the behaviour you expect. Iterative simulation in your case and most cases is a form of integration where errors build up fast and unpredictably.
Yes, these equations hold in 2D space, because your 2D space is just a 2D representation of a 3D world. (A "real" 2D universe would have different equations, but that's not relevant here.)
A long shot: Are you perhaps using distance to the surface of the planet as r?
If that isn't it, try cutting your time step in half; if that makes a big difference, keep reducing it until the behavior stops changing.
If that makes no difference, try setting the initial velocity to zero, then watching it fall for a few iterations and measuring its acceleration to see if it's GM/r2. If the answer still isn't clear, post the results and we'll try to figure it out.
For use in a rigid body simulation, I want to compute the mass and inertia tensor (moment of inertia), given a triangle mesh representing the boundary of the (not necessarily convex) object, and assuming constant density in the interior.
Assuming your trimesh is closed (whether convex or not) there is a way!
As dmckee points out, the general approach is building tetrahedrons from each surface triangle, then applying the obvious math to total up the mass and moment contributions from each tet. The trick comes in when the surface of the body has concavities that make internal pockets when viewed from whatever your reference point is.
So, to get started, pick some reference point (the origin in model coordinates will work fine), it doesn't even need to be inside of the body. For every triangle, connect the three points of that triangle to the reference point to form a tetrahedron. Here's the trick: use the triangle's surface normal to figure out if the triangle is facing towards or away from the reference point (which you can find by looking at the sign of the dot product of the normal and a vector pointing at the centroid of the triangle). If the triangle is facing away from the reference point, treat its mass and moment normally, but if it is facing towards the reference point (suggesting that there is open space between the reference point and the solid body), negate your results for that tet.
Effectively what this does is over-count chunks of volume and then correct once those areas are shown to be not part of the solid body. If a body has lots of blubbery flanges and grotesque folds (got that image?), a particular piece of volume may be over-counted by a hefty factor, but it will be subtracted off just enough times to cancel it out if your mesh is closed. Working this way you can even handle internal bubbles of space in your objects (assuming the normals are set correctly). On top of that, each triangle can be handled independently so you can parallelize at will. Enjoy!
Afterthought: You might wonder what happens when that dot product gives you a value at or near zero. This only happens when the triangle face is parallel (its normal is perpendicular) do the direction to the reference point -- which only happens for degenerate tets with small or zero area anyway. That is to say, the decision to add or subtract a tet's contribution is only questionable when the tet wasn't going to contribute anything anyway.
Decompose your object into a set of tetrahedrons around the selected interior point. (That is solids using each triangular face element and the chosen center.)
You should be able to look up the volume of each element. The moment of inertia should also be available.
It gets to be rather more trouble if the surface is non-convex.
I seem to have miss-remembered by nomenclature and skew is not the adjective I wanted. I mean non-regular.
This is covered in the book "Game Physics, Second Edition" by D. Eberly. The chapter 2.5.5 and sample code is available online. (Just found it, haven't tried it out yet.)
Also note that the polyhedron doesn't have to be convex for the formulas to work, it just has to be simple.
I'd take a look at vtkMassProperties. This is a fairly robust algorithm for computing this, given a surface enclosing a volume.
If your polydedron is complicated, consider using Monte Carlo integration, which is often used for multidimensional integrals. You will need an enclosing hypercube, and you will need to be able to test whether a given point is inside or outside the polyhedron. And you will need to be patient, as Monte Carlo integration is slow.
Start as usual at Wikipedia, and then follow the external links pages for further reading.
(For those unfamiliar with Monte Carlo integration, here's how to compute a mass. Pick a point in the containing hypercube. Add to the point_total counter. Is it in the polyhedron? If yes, add to the point_internal counter. Do this lots (see the convergence and error bound estimates.) Then
mass_polyhedron/mass_hypercube \approx points_internal/points_total.
For a moment of inertia, you weight each count by the square of the distance of the point to the reference axis.
The tricky part is testing whether a point is inside or outside your polyhedron. I'm sure that there are computational geometry algorithms for that.