clang - LLVM: Get function argument locations (ABI) -


i'd write llvm plugin tell me: each function declaration, how many general purpose register, xmm register, , stack arguments function have. needs work x86 sysv calling convention. possible? if so, direction appreciated.

it's possible tricky, llvm seems more friendly when attempt manipulate ir when messing machine specific code. there's no easy way add passes, one. note eventual number of registers used depends on how virtual registers allocated real x86 logical register, spilling may occur in cases, , elimination of variables in others. you're not prevented work on ir values in ssa form, need work on last stages of codegen. make things more interesting, depends on level of optimization use. check out - llvm/lib/codegen/passes.cpp, @ addoptimizedregalloc or addfastregalloc, check out passed called inside , use last ones (implemented in separate files in codegen), hitch ride on. internal loops should pretty straight forward, you'll need run bookkeeping based on x86 target regs enumerated in targetregisterinfo


Comments

Post a Comment

Popular posts from this blog

python - How to create a legend for 3D bar in matplotlib? -

Image
given ax = plt.subplot() : ax.bar()[0] can passed plt.legend() . however, ax.bar3d() returns none . how create legend displayed bars? update: passing legend="stuff" ax.bar3d() , calling ax.legend() raises /usr/lib/python2.6/site-packages/matplotlib/axes.py:4368: userwarning: no labeled objects found. use label='...' kwarg on individual plots. warnings.warn("no labeled objects found. " you need use proxy artist legends not supported. this code: from mpl_toolkits.mplot3d import axes3d import matplotlib.pyplot plt import numpy np fig = plt.figure() ax = fig.add_subplot(111, projection='3d') x, y = np.random.rand(2, 100) * 4 hist, xedges, yedges = np.histogram2d(x, y, bins=4) elements = (len(xedges) - 1) * (len(yedges) - 1) xpos, ypos = np.meshgrid(xedges[:-1]+0.25, yedges[:-1]+0.25) xpos = xpos.flatten() ypos = ypos.flatten() zpos = np.zeros(elements) dx = 0.5 * np.ones_like(zpos) dy = dx.copy() dz = hist.flatten() ax...
Read more

java - Multi-Label Document Classification -

i have database in store data based upon following 3 fields: id, text, {labels}. note each text has been assigned more 1 label \ tag \ class. want build model (weka \ rapidminer \ mahout) able recommend \ classify bunch of labels \ tags \ classes given text. i have heard svm , naive bayes classifier, not sure whether support multi-label classification or not. guides me right direction more welcome! the basic multilabel classification method one-vs.-the-rest (ovr), called binary relevance (br). basic idea take off-the-shelf binary classifier, such naive bayes or svm, create k instances of solve k independent classification problems. in python-like pseudocode: for each class k: learner = svm(settings) # example labels = [class_of(x) == k x in samples] learner.learn(samples, labels) then @ prediction time, run each of binary classifiers on sample , collect labels predict positive. (both training , prediction can done in parallel, since problems assumed ...
Read more

php - Dynamic url re-writing using htaccess -

how can rewrite http://mydomain.com/test/master.php?catid=2&subcatid=8 http://mydomain.com/test/master.php/catname/subcat using .htaccess file. once rewritten, how can access these parameters in master.php? note: untested, let me know if doesn't work. rewriterule ^master.php/([a-za-z0-9_-]+)/([a-za-z0-9_-]+)$ /master.php?catid$1&subcatid=$2 [l]
Read more