similar to: Understanding linear contrasts in Anova using R

quite some speed improvement indeed. attached the updated patch to apply to svn/trunk. j -------------- next part -------------- A non-text attachment was scrubbed... Name: theora-mmx.patch.gz Type: application/x-gzip Size: 8648 bytes Desc: not available Url : http://lists.xiph.org/pipermail/theora-dev/attachments/20040824/5a5f2731/theora-mmx.patch-0001.bin

Hello, Here is my first speedup patch. Like 10-11%. No IDCT yet. Please feel free to comment my code or even better think about improvements. :) I belive my routines are not so bad, maybe one day they will be even more faster. What needs to be optimized is the loop filter fuction. I have no ideas now how to do it. It does not leave much space for parallel stuff, copying memory from lot of

Hi, I'm new to Theora and would like to propose several performance optimization using advanced instructions in x86 CPUs (SSE2-SSE4.2). There are several source files in \x86 and \x86_vc which developed using inline assembler. However this cause several maintenance problems: 1) Need to sync gcc & msvc versions 2) Only 32bit environment is supported 3) No support for newer than MMX

On 20.10.2010 05:00, Jakob Stoklund Olesen wrote: > On Oct 19, 2010, at 6:37 PM, Roland Scheidegger wrote: > >> Thanks for giving it a look! >> >> On 19.10.2010 23:21, Jakob Stoklund Olesen wrote: >>> On Oct 19, 2010, at 11:40 AM, Roland Scheidegger wrote: >>> >>>> So I saw that the code is doing lots of register >>>>

Dear all, For an introductory course on glm?s I would like to create an example to show the difference between glm and transformation of the response. For this, I tried to create a dataset where the variance increases with the mean (as is the case in many ecological datasets): poissondata=data.frame( response=rpois(40,1:40), explanatory=1:40) attach(poissondata) However, I have run into

Thanks for giving it a look! On 19.10.2010 23:21, Jakob Stoklund Olesen wrote: > On Oct 19, 2010, at 11:40 AM, Roland Scheidegger wrote: > >> So I saw that the code is doing lots of register >> spilling/reloading. Now I understand that due to calling >> conventions, there's not really a way to avoid this - I tried using >> coldcc but apparently the backend

Is there any way to put an argument into an object name. For example, say I have 5 objects, model1, model2, model3, model4 and model5. I would like to make a vector of the r.squares from each model by code such as this: rsq <- summary(model1)$r.squared for(i in 2:5){ rsq <- c(rsq, summary(model%i%)$r.squared) } So I assign the first value to rsq then cycle through models 2 through

On Oct 20, 2010, at 7:46 AM, Roland Scheidegger wrote: > On 20.10.2010 05:00, Jakob Stoklund Olesen wrote: >> Look in X86InstrControl.td. The call instructions are all prefixed >> by: >> >> let Defs = [RAX, RCX, RDX, RSI, RDI, R8, R9, R10, R11, FP0, FP1, FP2, >> FP3, FP4, FP5, FP6, ST0, ST1, MM0, MM1, MM2, MM3, MM4, MM5, MM6, MM7, >> XMM0, XMM1, XMM2, XMM3,

(repost with right sender address) On 20.10.2010 18:13, Jakob Stoklund Olesen wrote: > On Oct 20, 2010, at 7:46 AM, Roland Scheidegger wrote: > >> On 20.10.2010 05:00, Jakob Stoklund Olesen wrote: >>> Look in X86InstrControl.td. The call instructions are all prefixed >>> by: >>> >>> let Defs = [RAX, RCX, RDX, RSI, RDI, R8, R9, R10, R11, FP0, FP1,

hello all, I am trying to use the function getCovariateFormula(nlme) in conjunction with the library lme4. When I load both packages I get the following message and the getCovariateFormula function no longer works: library(nlme) library(lme4) Attaching package 'lme4': The following object(s) are masked from package:nlme : contr.SAS getCovariateFormula

I am running an lme model with the main effects of four fixed variables (3 continuous and one categorical – see below) and one random variable. The data describe the densities of a mite species – awsm – in relation to four variables: adh31 (temperature related), apsm (another plant feeding mite) awpm (a predatory mite), and orien (sampling location within plant – north or south). I have read

On Oct 19, 2010, at 6:37 PM, Roland Scheidegger wrote: > Thanks for giving it a look! > > On 19.10.2010 23:21, Jakob Stoklund Olesen wrote: >> On Oct 19, 2010, at 11:40 AM, Roland Scheidegger wrote: >> >>> So I saw that the code is doing lots of register >>> spilling/reloading. Now I understand that due to calling >>> conventions, there's not

How do I get the TargetRegisterClass for a physical register? SSARegMap::getRegClass only works for virtual registers. -Dave

Take a look at getPhysicalRegisterRegClass( const MRegisterInfo *MRI, MVT::ValueType VT, unsigned reg) in ScheduleDAG.cpp. -- Christopher Lamb On Jun 18, 2007, at 4:52 PM, David A. Greene wrote: > How do I get the TargetRegisterClass for a physical register? > SSARegMap::getRegClass only works for virtual registers. > >

On Monday 18 June 2007 19:02, Christopher Lamb wrote: > Take a look at getPhysicalRegisterRegClass( > const MRegisterInfo *MRI, > MVT::ValueType VT, > unsigned reg) > > in ScheduleDAG.cpp. Yuck. I was afraid of that. What is the ValueType needed for? Isn't the register id itself an indication of the ValueType it represents? Where I'm at I

If I have a model line = lm(y~x1) and I want to use a for loop to change the number of explanatory variables, how would I do this? So for example I want to store the model objects in a list. model1 = lm(y~x1) model2 = lm(y~x1+x2) model3 = lm(y~x1+x2+x3) model4 = lm(y~x1+x2+x3+x4) model5 = lm(y~x1+x2+x3+x4+x5)... model10. model_function = function(x){ for(i in 1:x) { } If x =1, then the list

Hi LLVMers, I have finally sorted out licensing issues and found some time, so I'm trying to port my PBQP register allocator to 2.4 in order to contribute it (if you want it). I've run into a bug that has me confused though. I'm currently failing the following assertion: llc: VirtRegMap.cpp:1733: void<unnamed>::LocalSpiller::RewriteMBB(llvm::MachineBasicBlock&,

Dear R users, I am using lme and nlme to account for spatially correlated errors as random effects. My basic question is about being able to correct F, p, R2 and parameters of models that do not take into account the nature of such errors using gls, glm or nlm and replace them for new F, p, R2 and parameters using lme and nlme as random effects. I am studying distribution patterns of 50 tree

Hello, I would like to announce the semi-optimized oc_state_loop_filter_frag_rows It gains like 7% speedup. Unfortunately it has some issues: 1) wont compile on 64bit (I will fix it later hopefully) 2) is not yet fully optimized (instruction stalls) Here are the results. CPU: Athlon, speed 1466.91 MHz (estimated) Counted CPU_CLK_UNHALTED events (Cycles outside of halt state) with a unit mask

hello everybody. i need to log "who did what" on some models. i was reading recipe 59 of rails recipes and i created something like that: class LogSweeper < ActionController::Caching::Sweeper observe :model1, :model2, :model3, :model4, :model5, ... after_save(model) save_log(model, "save") end after_destroy(model) save_log(model, "destroy) end