文件列表:

.cproject (16037, 2015-10-11)
.project (825, 2015-10-11)
CMakeLists.txt (3051, 2015-10-11)
GNUmakefile (659, 2015-10-11)
cis565_rasterizer.launch (1532, 2015-10-11)
cmake (0, 2015-10-11)
cmake\CMakeParseArguments.cmake (5932, 2015-10-11)
cmake\FindCUDA.cmake (77972, 2015-10-11)
cmake\FindCUDA (0, 2015-10-11)
cmake\FindCUDA\make2cmake.cmake (3455, 2015-10-11)
cmake\FindCUDA\parse_cubin.cmake (3441, 2015-10-11)
cmake\FindCUDA\run_nvcc.cmake (11224, 2015-10-11)
cmake\FindPackageHandleStandardArgs.cmake (14816, 2015-10-11)
cmake\FindPackageMessage.cmake (2029, 2015-10-11)
external (0, 2015-10-11)
external\include (0, 2015-10-11)
external\include\GL (0, 2015-10-11)
external\include\GL\Copying.txt (1439, 2015-10-11)
external\include\GL\LICENSE.txt (3797, 2015-10-11)
external\include\GL\glew.h (1018809, 2015-10-11)
external\include\GL\glxew.h (73140, 2015-10-11)
external\include\GL\wglew.h (63383, 2015-10-11)
external\include\GLFW (0, 2015-10-11)
external\include\GLFW\COPYING.txt (934, 2015-10-11)
external\include\GLFW\glfw3.h (115094, 2015-10-11)
external\include\GLFW\glfw3native.h (10437, 2015-10-11)
external\include\glm (0, 2015-10-11)
external\include\glm\CMakeLists.txt (1468, 2015-10-11)
external\include\glm\common.hpp (1644, 2015-10-11)
external\include\glm\detail (0, 2015-10-11)
external\include\glm\detail\_features.hpp (13123, 2015-10-11)
external\include\glm\detail\_fixes.hpp (1983, 2015-10-11)
external\include\glm\detail\_noise.hpp (4348, 2015-10-11)
external\include\glm\detail\_swizzle.hpp (55046, 2015-10-11)
external\include\glm\detail\_swizzle_func.hpp (64653, 2015-10-11)
external\include\glm\detail\_vectorize.hpp (5055, 2015-10-11)
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CUDA Rasterizer =============== **University of Pennsylvania, CIS 565: GPU Programming and Architecture, Project 4** * (TODO) YOUR NAME HERE * Tested on: (TODO) Windows 22, i7-2222 @ 2.22GHz 22GB, GTX 222 222MB (Moore 2222 Lab) ### (TODO: Your README) *DO NOT* leave the README to the last minute! It is a crucial part of the project, and we will not be able to grade you without a good README. Instructions (delete me) ======================== This is due Sunday, October 11, evening at midnight. **Summary:** In this project, you will use CUDA to implement a simplified rasterized graphics pipeline, similar to the OpenGL pipeline. You will implement vertex shading, primitive assembly, rasterization, fragment shading, and a framebuffer. More information about the rasterized graphics pipeline can be found in the class slides and in the CIS 560 lecture notes. The base code provided includes an OBJ loader and much of the I/O and bookkeeping code. It also includes some functions that you may find useful, described below. The core rasterization pipeline is left for you to implement. You are not required to use this base code if you don't want to. You may also change any part of the base code as you please. **This is YOUR project.** **Recommendation:** Every image you save should automatically get a different filename. Don't delete all of them! For the benefit of your README, keep a bunch of them around so you can pick a few to document your progress. ### Contents * `src/` C++/CUDA source files. * `util/` C++ utility files. * `objs/` Example OBJ test files (# verts, # tris in buffers after loading) * `tri.obj` (3v, 1t): The simplest possible geometric object. * `cube.obj` (36v, 12t): A small model with low depth-complexity. * `suzanne.obj` (2904 verts, 968 tris): A medium model with low depth-complexity. * `suzanne_smooth.obj` (2904 verts, 968 tris): A medium model with low depth-complexity. This model has normals which must be interpolated. * `cow.obj` (17412 verts, 5804 tris): A large model with low depth-complexity. * `cow_smooth.obj` (17412 verts, 5804 tris): A large model with low depth-complexity. This model has normals which must be interpolated. * `flower.obj` (1920 verts, ***0 tris): A medium model with very high depth-complexity. * `sponza.obj` (837,489 verts, 279,163 tris): A huge model with very high depth-complexity. * `renders/` Debug render of an example OBJ. * `external/` Includes and static libraries for 3rd party libraries. ### Running the code The main function requires a scene description file. Call the program with one as an argument: `cis565_rasterizer objs/cow.obj`. (In Visual Studio, `../objs/cow.obj`.) If you are using Visual Studio, you can set this in the Debugging > Command Arguments section in the Project properties. Note that this value is different for every different configuration type. Make sure you get the path right; read the console for errors. ## Requirements **Ask on the mailing list for any clarifications.** In this project, you are given the following code: * A library for loading standard Alias/Wavefront `.obj` format mesh files and converting them to OpenGL-style buffers of index and vertex data. * This library does NOT read materials, and provides all colors as white by default. You can use another library if you wish. * Simple structs for some parts of the pipeline. * Depth buffer to framebuffer copy. * CUDA-GL interop. You will need to implement the following features/pipeline stages: * Vertex shading. * (Vertex shader) perspective transformation. * Primitive assembly with support for triangles read from buffers of index and vertex data. * Rasterization. * Fragment shading. * A depth buffer for storing and depth testing fragments. * Fragment to depth buffer writing (**with** atomics for race avoidance). * (Fragment shader) simple lighting scheme, such as Lambert or Blinn-Phong. See below for more guidance. You are also required to implement at least 3.0 "points" worth in extra features. (point values are given in parentheses): * (1.0) Tile-based pipeline. * Additional pipeline stages. * (1.0) Tessellation shader. * (1.0) Geometry shader, able to output a variable number of primitives per input primitive, optimized using stream compaction (thrust allowed). * (0.5 **if not doing geometry shader**) Backface culling, optimized using stream compaction (thrust allowed). * (1.0) Transform feedback. * (0.5) Scissor test. * (0.5) Blending (when writing into framebuffer). * (1.0) Instancing: draw one set of vertex data multiple times, each run through the vertex shader with a different ID. * (0.5) Correct color interpolation between points on a primitive. * (1.0) UV texture mapping with bilinear texture filtering and perspective correct texture coordinates. * Support for rasterizing additional primitives: * (0.5) Lines or line strips. * (0.5) Points. * (1.0) Anti-aliasing. * (1.0) Occlusion queries. * (1.0) Order-independent translucency using a k-buffer. * (0.5) **Mouse**-based interactive camera support. This extra feature list is not comprehensive. If you have a particular idea you would like to implement, please **contact us first**. **IMPORTANT:** For each extra feature, please provide the following brief analysis: * Concise overview write-up of the feature. * Performance impact of adding the feature (slower or faster). * If you did something to accelerate the feature, what did you do and why? * How might this feature be optimized beyond your current implementation? ## Base Code Tour You will be working primarily in two files: `rasterize.cu`, and `rasterizeTools.h`. Within these files, areas that you need to complete are marked with a `TODO` comment. Areas that are useful to and serve as hints for optional features are marked with `TODO (Optional)`. Functions that are useful for reference are marked with the comment `CHECKITOUT`. **You should look at all TODOs and CHECKITOUTs before starting!** There are not many. * `src/rasterize.cu` contains the core rasterization pipeline. * A few pre-made structs are included for you to use, but those marked with TODO will also be needed for a simple rasterizer. As with any part of the base code, you may modify or replace these as you see fit. * `src/rasterizeTools.h` contains various useful tools * Includes a number of barycentric coordinate related functions that you may find useful in implementing scanline based rasterization. * `util/utilityCore.hpp` serves as a kitchen-sink of useful functions. ## Rasterization Pipeline Possible pipelines are described below. Pseudo-type-signatures are given. Not all of the pseudocode arrays will necessarily actually exist in practice. ### First-Try Pipeline This describes a minimal version of *one possible* graphics pipeline, similar to modern hardware (DX/OpenGL). Yours need not match precisely. To begin, try to write a minimal amount of code as described here. Verify some output after implementing each pipeline step. This will reduce the necessary time spent debugging. Start out by testing a single triangle (`tri.obj`). * Clear the depth buffer with some default value. * Vertex shading: * `VertexIn[n] vs_input -> VertexOut[n] vs_output` * A minimal vertex shader will apply no transformations at all - it draws directly in normalized device coordinates (-1 to 1 in each dimension). * Primitive assembly. * `VertexOut[n] vs_output -> Triangle[n/3] primitives` * Start by supporting ONLY triangles. For a triangle defined by indices `(a, b, c)` into `VertexOut` array `vo`, simply copy the appropriate values into a `Triangle` object `(vo[a], vo[b], vo[c])`. * Rasterization. * `Triangle[n/3] primitives -> Fragment[m] rasterized` * A scanline implementation is simple to start with. * Parallelize over triangles, but for now, loop over every pixel in each thread. * Note that you won't have any real allocated array of size `m`. * Fragments to depth buffer. * `Fragment[m] rasterized -> Fragment[width][height] depthbuffer` * `depthbuffer` is for storing and depth testing fragments. * Results in race conditions - don't bother to fix these until it works! * Can really be done inside the fragment shader, if you call the fragment shader from the rasterization kernel for every fragment (including those which get occluded). **OR,** this can be done before fragment shading, which may be faster but means the fragment shader cannot change the depth. * Fragment shading. * `Fragment[width][height] depthbuffer ->` * A super-simple test fragment shader: output same color for every fragment. * Also try displaying various debug views (normals, etc.) * Fragment to framebuffer writing. * `-> vec3[width][height] framebuffer` * Simply saves the fragment shader results into the framebuffer (to be displayed on the screen). Where you have the following data structure: ### A Useful Pipeline * Clear the depth buffer with some default value. * You should be able to pass a default value to the clear function, so that you can set the clear color (background), clear depth, etc. * Vertex shading: * `VertexIn[n] vs_input -> VertexOut[n] vs_output` * Apply some vertex transformation (e.g. model-view-projection matrix using `glm::lookAt ` and `glm::perspective `). * Primitive assembly. * `VertexOut[n] vs_output -> Triangle[n/3] primitives` * As above. * Other primitive types are optional. * Rasterization. * `Triangle[n/3] primitives -> Fragment[m] rasterized` * You may choose to do a tiled rasterization method, which should have lower global memory bandwidth. It will also change other parts of the pipeline. * Parallelize over triangles, but now avoid looping over all pixels: * When rasterizing a triangle, only scan over the box around the triangle (`getAABBForTriangle`). * Fragments to depth buffer. * `Fragment[m] rasterized -> Fragment[width][height] depthbuffer` * `depthbuffer` is for storing and depth testing fragments. * This can be done before fragment shading, which prevents the fragment shader from changing the depth of a fragment. * This order results in an optimization: it allows you to do depth tests before spending execution time in complex fragment shader code! * If you want to be able to change the depth of a fragment, you'll have to make an adaptation. For example, you can add a separate shader stage which occurs during rasterization, which can change the depth. Or, you can call the fragment shader from the rasterization step - but be aware that the performance will be much worse - occupancy will be low due to the variable run length of each thread. * Handle race conditions! Since multiple primitives write fragments to the same fragment in the depth buffer, races must be avoided by using CUDA atomics. * *Approach 1:* Lock the location in the depth buffer during the time that a thread is comparing old and new fragment depths (and possibly writing a new fragment). This should work in all cases, but be slower. See the section below on implementing this. * *Approach 2:* Convert your depth value to a fixed-point `int`, and use `atomicMin` to store it into an `int`-typed depth buffer `intdepth`. After that, the value which is stored at `intdepth[i]` is (usually) that of the fragment which should be stored into the `fragment` depth buffer. * This may result in some rare race conditions (e.g. across blocks). * The `flower.obj` test file is good for testing race conditions. * Fragment shading. * `Fragment[width][height] depthbuffer ->` * Add a shading method, such as Lambert or Blinn-Phong. Lights can be defined by kernel parameters (like GLSL uniforms). * Fragment to framebuffer writing. * `-> vec3[width][height] framebuffer` * Simply copies the colors out of the depth buffer into the framebuffer (to be displayed on the screen). This is a suggested sequence of pipeline steps, but you may choose to alter the order of this sequence or merge entire kernels as you see fit. For example, if you decide that doing has benefits, you can choose to merge the vertex shader and primitive assembly kernels, or merge the perspective transform into another kernel. There is not necessarily a right sequence of kernels, and you may choose any sequence that works. Please document in your README what sequence you choose and why. ## Resources ### CUDA Mutexes Adapted from [this StackOverflow question](http://stackoverflow.com/questions/21341495/cuda-mutex-and-atomiccas). ``` __global__ void kernelFunction(...) { // Get a pointer to the mutex, which should be 0 right now. unsigned int *mutex = ...; // Loop-wait until this thread is able to execute its critical section. bool isSet; do { isSet = (atomicCAS(mutex, 0, 1) == 0); if (isSet) { // Critical section goes here. // The critical section MUST be inside the wait loop; // if it is afterward, a deadlock will occur. } if (isSet) { mutex = 0; } } while (!isSet); } ``` ### Links The following resources may be useful for this project. * Line Rasterization slides, MIT EECS 6.837, Teller and Durand * [Slides](http://groups.csail.mit.edu/graphics/classes/6.837/F02/lectures/6.837-7_Line.pdf) * High-Performance Software Rasterization on GPUs * [Paper (HPG 2011)](http://www.tml.tkk.fi/~samuli/publications/laine2011hpg_paper.pdf) * [Code](http://code.google.com/p/cudaraster/) * Note that looking over this code for reference with regard to the paper is fine, but we most likely will not grant any requests to actually incorporate any of this code into your project. * [Slides](http://bps11.idav.ucdavis.edu/talks/08-gpuSoftwareRasterLaineAndPantaleoni-BPS2011.pdf) * The Direct3D 10 System (SIGGRAPH 2006) - for those interested in doing geometry shaders and transform feedback * [Paper](http://dl.acm.org/citation.cfm?id=1141947) * [Paper, through Penn Libraries proxy](http://proxy.library.upenn.edu:2247/citation.cfm?id=1141947) * Multi-Fragment Effects on the GPU using the k-Buffer - for those who want to do order-independent transparency using a k-buffer * [Paper](http://www.inf.ufrgs.br/~comba/papers/2007/kbuffer_preprint.pdf) * FreePipe: A Programmable, Parallel Rendering Architecture for Efficient Multi-Fragment Effects (I3D 2010) * [Paper](https://sites.google.com/site/hmcen0921/cudarasterizer) * Writing A Software Rasterizer In Javascript * [Part 1](http://simonstechblog.blogspot.com/2012/04/software-rasterizer-part-1.html) * [Part 2](http://simonstechblog.blogspot.com/2012/04/software-rasterizer-part-2.html) ## Third-Party Code Policy * Use of any third-party code must be approved by asking on our Google Group. * If it is approved, all students are welcome to use it. Generally, we approve use of third-party code that is not a core part of the project. For example, for the path tracer, we would approve using a third-party library for loading models, but would not approve copying and pasting a CUDA function for doing refraction. * Third-party code **MUST** be credited in README.md. * Using third-party code without its approval, including using another student's code, is an academic integrity violation, and will, at minimum, result in you receiving an F for the semester. ## README Replace the contents of this README.md in a clear manner with the following: * A brief description of the project and the specific features you implemented. * At least one screenshot of your project running. * A 30 second or longer video of your project running. * A performance analysis (described below). ### Performance Analysis The performance analysis is where you will investigate how to make your CUDA programs more efficient using the skills you've learned in class. You must have performed at least one experiment on your code to investigate the positive or negative effects on performance. We encourage you to get creative with your tweaks. Consider places in your code that could be considered bottlenecks and try to improve them. Provide summary of your optimizations (no more than one page), along with tables and or graphs to visually explain any performance differences. * Include a breakdown of time spent in each pipeline stage for a few different models. It is suggested that you use pie charts or 100% stacked bar charts. * For optimization steps (like backface culling), include a performance comparison to show the effectiveness. ## Submit If you have modified any of the `CMakeLists.txt` files at all (aside from the list of `SOURCE_FILES`), you must test that your project can build in Moore 100B/C. Beware of any build issues discussed on the Google Group. 1. Open a GitHub pull request so that we can see that you have finished. The title should be "Submission: YOUR NAME". * **ADDITIONALLY:** In the body of the pull request, include a link to your repository. 2. Send an email to the TA (gmail: kainino1+cis565@) with: * **Subject**: in the form of `[CIS565] Project N: PENNKEY`. * Direct link to your pull request on GitHub. * Estimate the amount of time you spent on the project. * If there were any outstanding problems, or if you did any extra work, *briefly* explain. * Feedback on the project itself, if any.

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