Mercurial > hg > CbC > CbC_llvm
diff polly/www/documentation/gpgpucodegen.html @ 150:1d019706d866
LLVM10
| author | anatofuz |
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| date | Thu, 13 Feb 2020 15:10:13 +0900 |
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| children | 0572611fdcc8 |
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--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/polly/www/documentation/gpgpucodegen.html Thu Feb 13 15:10:13 2020 +0900 @@ -0,0 +1,229 @@ +<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01//EN" + "http://www.w3.org/TR/html4/strict.dtd"> +<!-- Material used from: HTML 4.01 specs: http://www.w3.org/TR/html401/ --> +<html> +<head> + <META http-equiv="Content-Type" content="text/html; charset=ISO-8859-1"> + <title>Polly - GPGPU Code Generation</title> + <link type="text/css" rel="stylesheet" href="../menu.css"> + <link type="text/css" rel="stylesheet" href="../content.css"> +</head> +<body> +<div id="box"> +<!--#include virtual="../menu.html.incl"--> +<div id="content"> + <!--*********************************************************************--> + <h1>Polly - GPGPU Code Generation</h1> + <!--*********************************************************************--> +<p><em>WARNING: This project was part of the Google Summer of Code 2012. +It is currently not finished, but it is in the design and implementation stage. +The ideas/plans described here may not yet be implemented in Polly and may +change later on.</em></p> + +This project adds GPGPU code generation feature to Polly. + +<h2>Objective</h2> +<p>The overall objective of this GSoC project is to create a preliminary + implementation of GPGPU code generation for Polly. With this addition, users + can parallelize some perfectly nested loops with Polly to execute on a + heterogeneous platform, composed of CPU and GPU.</p> +<p>There are several successful projects about automatic source-to-source gpu + code transformation. C-to-CUDA[1] uses the standard Pluto algorithms for + computing an affine schedule and then applies a wavefront transformation to + obtain one sequential and n-1 parallel loops. The parallel loops are then + mapped onto the blocks and threads of GPU. PPCG[2] introduces some advanced + algorithms which can expose much more parallelism than other methods . And It + also introduces affine partition heuristics and code generation algorithms + for locality enhancement in the registers and shared memory.</p> +<p>Since automatic GPGPU code generation is quite a complex problem and what we + target is a low-level intermediate representation, LLVM IR, rather than a + high-level language source, it is important for us to set a proper objective + as a start step to give a complete solution to GPGPU code generation for LLVM + IR.</p> +<p>Firstly, we plan to target two kinds of relatively simple test cases. One is + comprised of pure parallel and perfectly nested loops, like the following + code.</p> +<pre> +parfor(int i=0 to M) + parfor(int j=0 to N) + LoopBody(i, j); +</pre> +<p>Another one is that all the loops in it are parallel except the inner-most + one, just like this:</p> +<pre> +parfor(int i=0 to M) + parfor(int j=0 to N) + non-parfor(int k=0 to K) + LoopBody(i, j, k); +</pre> +<p>The LoopBody part should be limited to instructions or functions calls + (intrinsics) which can be handled by LLVM's NVPTX backend.</p> +<p>On the other hand, we focus on building a preliminary and scalable framework + of GPGPU code generation for polly. Thus we plan to employ relatively simple + tiling and mapping algorithms and optimize them later.</p> +<h2>Work Flow</h2> +<h3>GPGPU Code Generation In General</h3> +<p>C-to-CUDA[1] and PPCG[2] propose similar steps to solve the automatic GPGPU + code generation problem.</p> +<li>Look for parallel loops.</li> +<li>Create a polyhedral model from the loops.</li> +<li>Tile and map the loops to GPU blocks and threads.</li> +<li>Determine where to place the data.</li> +<h3>What has been done in Polly</h3> +<p>Polly has implemented the 1st, 2nd and part of the 3rd of the above steps and + many other analysis and transformation passes.</p> +<h3>What to do in Polly</h3> +<p>Unlike many source-to-source optimizers such as C-to-CUDA and PPCG, Polly is + a low-level optimizer, which means we can't use a source-level compiler + (e.g. NVCC) to generate the final assembly for the device. We need manually + insert device driver API calls to execute the generated kernel assembly + text.</p> +<p>In this project, we assume that the device driver library has provided an + interface to launch kernels in the form of assembly text. Fortunately, most + of the mainstream GPU vendors provide such a feature in thier products (see + ptxjit of NVIDIA GPUs and CAL of AMD GPUs). Generally speaking, what we + are going to do in Polly is:</p> +<li>Find a way to tile the parallel loops.</li> +<li>Find a way to extract the loop body and transform it into thread-centric + parallel code.</li> +<li>Find a way to store/load the thread-centric code into/from a device module. +<li>Find a way to pass the target machine information and generate code of the + device module for the target. +<li>Find a way to map the tiled loop to GPU blocks and threads.</li> +<li>Find a way to insert CUDA synchronization operations on-demand. +<li>Find a way to generate the memory copy operations between a host and a + device.</li> +<li>Implement/Wrap a runtime library to serve as the execution engine for the + generated device code.</li> + +<h3>The Work Flow</h3> +<p>In this section, we assume that the host cpu is X86 and the device is NVIDIA + CUDA-compatible. we will use the following test case to describe our work + flow.</p> +<pre> +for(i = 0; i < 128; i++) + for(j = 0; j < 128; j++) + A[i][j] = i*128 + j; +</pre> +<p>The work flow of our code generator is as follows.</p> +<p>1.We first use Polly's jscop file importer to get a wanted 4-level parallel + tiled code.</p> +The "schedule" part of the pre-optimization jscop file is as the following: +<pre> +"schedule" : "{ Stmt_for_body3[i0, i1] -> schedule[0, i0, 0, i1, 0] }" +</pre> +The jscop file describing the tiling transformation is: +<pre> +"schedule" : "{ Stmt_for_body3[i0, i1] -> schedule[0, o0, o1, o2, o3]: + o0 >= 0 and o0 <= 7 and o1 >= 0 and o1 <= 15 and + o2 >= 0 and o2 <= 7 and o3 >= 0 and o3 <= 15 and + i0 = 16o0 + o1 and i1 = 16o2 + o3 }" +</pre> +We can test the schedule with the following command line. +<pre> +opt -load /path/to/polly/build/LLVMPolly.so -basicaa -polly-import-jscop + -polly-ast -analyze -q ./test.ll + -polly-import-jscop-postfix=transformed+gpu +</pre> +The output of this schedule is: +<pre> +for (c2=0;c2<=7;c2++) { + for (c3=0;c3<=15;c3++) { + for (c4=0;c4<=7;c4++) { + for (c5=0;c5<=15;c5++) { + Stmt_for_body3(16*c2+c3,16*c4+c5); + } + } + } +} +</pre> +Now we get a 4-dimensional parallel loops with a single SCoP statement in it. +<p>2.We then extract the loop body (or the inner-most non-parallel loop) into a + LLVM function, tagging it with PTX_Kernel call convention.</p> +<p>3.We extract the PTX_kernel function into a temporary module, set the target + triple (e.g. nvptx64-unknown-linux) for the module, transform the temporary + module into a string, store it in the original module and erase the + PTX_kernel function.</p> +<p>4.We replace the loops with their GPGPU counterpart. The GPGPU part of code + is composed of a call to the llvm.codegen intrinsic and function calls to our + GPU runtime library.</p> +<p>5.Finally, we generate the executable program with <em>llc</em> or run the + optimized LLVM IRs with a JIT compiler like <em>lli</em>.</p> +<h2>Usage</h2> +<p>1. Apply the llvm.codegen intrinsic patch to LLVM code base.</p> +<pre>cd /path/to/llvm/source +git am /path/to/polly/source/utils/0001-Add-llvm.codegen-intrinsic.patch</pre> +<p>2. Build the test case.</p> +<pre>/path/to/polly/source/test/create_ll.sh test.c</pre> +<p>3. Get and edit the jscop file (take function "gpu_codegen" as an example). +</p> +<pre>opt -load /path/to/polly/build/lib/LLVMPolly.so -basicaa + -polly-export-jscop ./test.ll +cp gpu_codegen___%for.cond---%for.end8.jscop + gpu_codegen___%for.cond---%for.end8.jscop.transformed+gpu +vi gpu_codegen___%for.cond---%for.end8.jscop.transformed+gpu</pre> +<p><em>(Please refer to section "The Work Flow" on how to edit the "schedule" + part of a statement)</em></p> +<p>4. Optimize the code with GPGPU code generation.</p> +<pre>opt -load /path/to/polly/build/lib/LLVMPolly.so -basicaa + -polly-import-jscop-postfix=transformed+gpu -enable-polly-gpgpu + -polly-gpgpu-triple=nvptx64-unknown-unknown -polly-codegen ./test.ll -S + -o test.gpued.ll</pre> +<p>5. Build the final assembly and executable.</p> +<pre>llc test.gpued.ll -o test.s +gcc test.s -lGPURuntime -o test</pre> +<p><em>(Please make sure that LD_LIBRARY_PATH is set properly so that + /path/to/polly/build/lib/libGPURuntime.so is visible to gcc.)</em></p> +<h2>TODO List</h2> + +<table class="wikitable" cellpadding="2"> +<tbody> +<tr style="background: rgb(239, 239, 239)"> + <th width="400px"> Tasks</th> + <th width="150px"> Status </th> + <th> Owner </th> +</tr> +<tr> +<th align="left">Tiling the Parallel Loops with An External Jscop File</th> +<td align="center" class='open'>Open, In Design</td> +<td>Yabin Hu</td> +</tr> +<tr> +<th align="left">GPU Runtime Library Implementation</th> +<td align="center" class='inprogress'>Coding Finished, In Reviewing</td> +<td></td> +</tr> +<tr> +<th align="left">llvm.codegen Intrinsic Implementation</th> +<td align="center" class='inprogress'>Codeing Finished, To Be Reviewed</td> +<td></td> +</tr> +<tr> +<th align="left">Code Generation For Host</th> +<td align="center" class='inprogress'>50% Done</td> +<td></td> +</tr> + +</tbody></table> + +<h2>References</h2> +<li type="1" value="1"> +<em>Automatic C-to-CUDA Code Generation for Affine Programs. </em><br /> + Muthu Manikandan Baskaran, J. Ramanujam and P. Sadayappan.<br /> + International Conference on Compiler Construction (CC) 2010.<br /> +</li> +<li type="1"><em>PPCG Project</em><br /> +<a href="http://freecode.com/projects/ppcg">http://freecode.com/projects/ppcg +</a></li> +<li type="1"> +<em>Where is the Data? Why You Cannot Debate GPU vs. CPU Performance Without the + Answer. </em><br /> + Chris Gregg and Kim Hazelwood<br /> + International Symposium on Performance Analysis of Systems and Software + (ISPASS) 2011. +</li> +<p></p> +</div> +</div> +</body> +</html>