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Introduction to Acceleration Structures
Keywords: ray-tracing, bounding box, grid, BVH, space partitioning data structure, k-d tree, octree, spatial division, spatial coherence, space tracing, 3D-Digital Differential Analyser, DDA.

This lesson is just a gentle introduction to the topic of acceleration structure for ray tracing. The fastest and most efficient acceleration structures will be presented in a separate lesson.

Introduction

Rendering the teapot was not as such a necessity for this series of basic lessons as it would normally be considered more as an advanced topic. However beside given us an opportunity to learn about the idea that curves and surfaces can be defined in a very compact way using control points weighted by some basis functions (a principle reused by many advanced rendering or shading techniques), it is also very useful to demonstrate that ray tracing is slow as the number of polygons/triangles and objects in the scene increases. The teapot has the advantage of resulting in the creation of 32 polygon grids which we can see as 32 different objects, something that we couldn't have obtained without supporting a parser to read geometry files (which we would rather prefer to ignore for the time being). Because of its increased complexity, this scene now takes a significant amount of time to render. Ray tracers are known for being slow but hopefully a lot of research has also been carried out to address this problem. Most techniques to speed up renders are based on acceleration structures. The most expensive task in a ray tracer is the intersection test. It is a costly operation which is potentially repeated a very large number of times (for each pixel of the frame we need to test all the triangles from the scene). In "Accelerated Ray Tracing" (1983), Fujimoto writes:

"The calculation speed of the ray-tracing method is undoubtedly one of the basic problems that must be dealt with. Why is raytracing so computationally expensive? The main cause was clearly identified at the very moment ray tracing first entered the field of computer graphics. According to Whitted, for simple scenes 75 percent of the total time is spent on calculating intersections between rays and objects. For more complex scenes the proportion goes as high as 95 percent. The time that must be spent calculating the intersections is directly related to the number of objects involved in the-scene".

Thus, to save time, we need to find ways of reducing this number of intersection tests as much as possible. The principle of acceleration structures, is to help deciding as quickly as possible which objects from the scene a particular ray is likely to intersect and reject large group of objects which we know for certain the ray will never hit. If, with such structure, we can reduce for instance the number of objects that a ray has to test by 50%, then theoretically, we should also roughly cut the render time by two.

Adding Statistics to the Ray Tracer

In order to measure the efficiency of the different acceleration methods we will test in this lesson, we need to be able to compare the render time of a frame with and without acceleration. Gathering some additional statistics like the total number of rays cast in the scene (which is usually directly related to the total render time), the number of times the ray-triangle intersections test has been executed and the number of ray-triangles hits can also give some interesting information: for instance how does the acceleration scheme perform, and which part of the rendering process takes the most time. Making changes to the code to support basic statistics gathering is really straightforward. We won't implement anything fancy here, just a few globals variables to count the number of rays, the number of times the ray-triangle intersection routine is called and the number of ray-triangle hits. Using global variables can be a problem when the application is multi-threaded which is not the case of our code yet. However in the anticipation of this eventuality, we will use atomic operations to modify the content of these variables.

Race conditions may occur when several processors try to update the content of a variable at the same time. Incrementing a variable for example requires to read the variable from memory, increment the value and write the result back to memory. If two processors try to increment a variable v "at the same time", the following sequence of events could happen:
  • processor 1 reads variable v from memory (let's assume v = 0) and stalls.
  • processor 2 reads variable v from memory = 0, increments the value and writes the result back to memory. The value of v is now 1.
  • processor 1 wakes up, increments the value of v which for processor 1 is 0, increment it and write the result to memory. The value of v is still 1, even though it should normally be 2.
It is not possible to stop processor 2 from changing the content of the variable until processor 1 has completed its add operation unless we use a mechanism like a mutex which is overkilled for such simple tasks. For low level tasks such as addition or subtraction, a much better choice to avoid a race condition, is to use atomic operations which have been added to the C++11 standard. Other methods can be used but this is one is really simple to implement. If you are not completely familiar with these concepts, read the lesson on multi-threading.

As for computing the total render time, we can simply keep track of time before the render starts and take the difference with the current time once the frame is finished. In our current implementation, we use the clock() function which does give the CPU time, not the real time. We use the function __sync_fetch_and_add to perform an atomic add (line 10 and 14).

While the following code is still valid, you should now be using the STL C++ atomic library which has been introduced in C++11. Check the lesson on Parallel Rendering for more recent information on this topic. This code will be revised once the basic section is complete (July 2014).

static uint64_t numRayTrianglesTests = 0; static uint64_t numRayTrianglesIsect = 0; static uint64_t numPrimaryRays = 0; bool intersectTriangle( const Ray &r, const Vec3f &v0, const Vec3f &v1, const Vec3f &v2, float &t, float &u, float &v) const { __sync_fetch_and_add(&numRayTrianglesTests, 1); Vec3f edge1 = v1 - v0; ... t = dot(edge2, qvec) * invDet; __sync_fetch_and_add(&numRayTrianglesIsect, 1); return true; } int main(int argc, char **argv) { clock_t timeStart = clock(); ... render(rc, filename); ... clock_t timeEnd = clock(); printf("Render time : %04.2f (sec)\n", (float)(timeEnd - timeStart) / CLOCKS_PER_SEC); printf("Total number of triangles : %d\n", totalNumTris); printf("Total number of primary rays : %lu\n", numPrimaryRays); printf("Total number of ray-triangles tests : %lu\n", numRayTrianglesTests); printf("Total number of ray-triangles intersections : %lu\n", numRayTrianglesIsect); return 0; }

We now have some tools to measure how efficient these acceleration structures are (and compare them to each other, an exercise which is not always very fair. As we will see, the performance of an acceleration method often depends on the scene: a structure which performs well for one particular setup can perform poorly for another. Running our ray tracing with these additions should print out the following statistics at the end of the render:

Render time : 138.75 (sec) Total number of triangles : 16384 Total number of primary rays : 307200 Total number of ray-triangles tests : 5033164800 Total number of ray-triangles intersections : 111889

As expected, the ratio between the number of ray-triangle intersection tests performed and the actual number of hits is really low: 0.002 percent! Let's now see how we can already make things run much faster with some very simple changes.