similar to: [LLVMdev] Advice - llvm as binary to binary translator ?

First, is there a way to search the archives for this list ? I apologize in advance if I have stepped on a FAQ. My goal is to execute legacy binary machine code from a very old one of a kind computer on a variety of modern computers. I already wrote an emulator for the legacy machine that executes the old machine code. However, my emulator is just an interpreter and therefore has

Hi Eric, I'm currently writing an IA-32 to LLVMIR translator. I'm only mid way through, but I can certainly say that there have been more difficulties than I anticipated when I began! I think that it is a reasonable approach, perhaps especially in your case, since you have an emulator already. Automatic static translation is equivalent to the halting problem for IA-32 code, though

Hi again, Thanks for the prompt reply. Just for the record i am running debian unstable/sid with nut 2.7.4-3 # dpkg -l 'nut*' | grep ^ii ii nut 2.7.4-3 all network UPS tools - metapackage ii nut-client 2.7.4-3 amd64 network UPS tools - clients ii nut-server 2.7.4-3 amd64 network UPS tools - core

Hello all, About a month ago Peter and Charles were kind enough to try to help me with getting a Tripp Lite USB UPS to work with NUT. I reported quite a bit of initial success, and then other things here fell apart. Between work, fence building and a week-long out of town business trip, I have had to drop this from my list of things to do lately. I am back at it, and I believe I will have

Folks I have modified an existing function to calculate 'ec/ld/lc' 50 values and their associated Fieller's confidence limits. It is based on EC50.calc (writtien by John Bailer) - but also borrows from the dose.p (MASS) function. My goal was to make the original EC50.calc function flexible with respect to 1) probability at which to calculate the expected dose, and 2) the link

Hello, I am trying to simulate binary outcome data for a logistic regression Monte Carlo study. I need to eventually be able to manipulate the structure of the error term to give groups of observations a random effect. Right now I am just doing a very basic set up to make sure I can recover the parameters properly. I am running into trouble with the code below. It works if you take out the object

Dear all, I have encountered some strange things when creating lm objects in R: model depends on the order of the terms specified in a formula. Let us consider the following simple example: > dat <- expand.grid(A = factor(c("a1", "a2")), + B = factor(paste("b", 1:4, sep="")), + rep = factor(1:2)) >

I'm sure this must be a nls() newbie question, but I'm stumped. I'm trying to do the example from Draper and Yang (1997). They give this snippet of S-Plus code: Specify the weight function: weight < - function(y,x1,x2,b0,b1,b2) { pred <- b0+b1*x1 + b2*x2 parms <- abs(b1*b2)^(1/3) (y-pred)/parms } Fit the model gmfit < -nls(~weight(y,x1,x2,b0,b1,b2),

Hi, I've made a research about how to compare two regression line slopes (of y versus x for 2 groups, "group" being a factor ) using R. I knew the method based on the following statement : t = (b1 - b2) / sb1,b2 where b1 and b2 are the two slope coefficients and sb1,b2 the pooled standard error of the slope (b) which can be calculated in R this way: > df1 <-

R-helpers: I have a data frame containing 4 factor variables (let's say A,B,C, and D) and 1 numerical variable (N). I would like to produce a cross-tabulated data frame in which A,B,C are individual columns, each factor of D is its own column, and the field is calculated as a given function of N (I would like to have two output data frames, one with the mean(N) and one with the

Hi, I was wondering why anova() and drop1() give different tail probabilities for F tests. I guess overdispersion is calculated differently in the following example, but why? Thanks for any advice, Tom For example: > x<-c(2,3,4,5,6) > y<-c(0,1,0,0,1) > b1<-glm(y~x,binomial) > b2<-glm(y~1,binomial) > drop1(b1,test="F") Single term deletions Model: y ~

I have design with two repeated-measures factor, and no grouping factor. I can analyze the dataset successfully in other software, including my legacy DOS version BMDP, and R's 'aov' function. I would like to use 'Anova' in 'car' in order to obtain the sphericity tests and the H-F corrected p-values. I do not believe the data are truly deficient in rank. I

Hello, I've some questions concerning log-transformations and plotting of the regression lines. So far as I know is it a problem to log-transform values smaller than 1 (0-1). In my statistics lecture I was told to do a log(x+1) transformation in such cases. So I provide here a small example to explain my questions: # Some example data for testing a1

Hello List! I am looking at top-down vs. bottom-up list scheduling for simple(r) in-order cores. First, for some context, below is a fairly representative pseudo-code example of the sort of DSP-like codes I am looking at: uint64_t foo(int *pA, int *pB, unsigned N, unsigned C) { uint64_t sum = 0; while (N-- > 0) { A1 = *pA++; A2 = *pA++; B1 = *pB++; B2 =

Hi list, I'm planning and testing a distributed asterisk deployment throughout several sites; each will be connected to the PSTN and all of them among themselves via IAX trunks. Phones will be SIP. I guess I already "solved" (worked-around, actually) asterisk's codec negotiation limitations regarding local G.711 utilization vs. remote G.729 while minimizing

I am attempting to use optim to solve a neural network problem. I would like to optimize coefficients that are currently stored in a matrix Y=270 x 1 X= 27- x 14 b1= 10x14 b2= 11x1 V= 10 x 14 set of prior variances. I have the following function: posterior.mode1=function(y,X,b_0,b2,V) { log.like=function(b1) { a_g=compute(b1) z_g=tanh(a_g); z_g=cbind(1,z_g)

Hello everyone, Charles suggested (about a week ago) that I repost to this list. I took a moment to run some additional tests ... The basics: -- UPS: Liebert PowerSure PSA 500 (from the 230 VAC / 50 Hz line) -- Kernel: 2.6.11.5 (from sources), USB support (down to and including CONFIG_USB_HIDDEV) compiled in statically (not as a module) -- Rest of OS: Basically still from the original SuSE

Hi all,,Im using function arima() I.e series is my data model<-arima(series,c(1,0,0)) forecast<-predict(model,80) I want to create a variable: b1<-forecast$pred - 1.96*forecast$se and save in a txt file but using this: save(b1, file= "b1.txt") creates afile butwith this inside: ]{HQ ~|LJIiW*-l)% )m#), RIiSfdbGur9p94; H"L#Rez 1y3pN8{,I6W!6= {6l?OMw_5KZ+ =

Hi I searched in the list and only found questions without answers e.g. http://finzi.psych.upenn.edu/R/Rhelp02a/archive/19955.html : Is there a way to get the same results with lme as with aov with Error()? Can anybody reproduce the following results with lme: id<-c(1,1,1,2,2,2,3,3,3,4,4,4,5,5,5,1,1,1,2,2,2,3,3,3,4,4,4,5,5,5,1,1,1,2,2,2,3,3,3,4,4,4,5,5,5)

Hi, My xen guest stopped booting suddenly and giving me the below error message. Any idea what is going wrong here? DOM 0 boots OK though. ata5.00: exception Emask 0x0 SAct 0x1 SErr 0x0 action 0x0 ata5.00: irq_stat 0x40000008 ata5.00: failed command: READ FPDMA QUEUED ata5.00: cmd 60/00:00:cd:ee:36/02:00:09:00:00/40 tag 0 ncq 262144 in res 51/40:72:5b:f0:36/d9:00:09:00:00/40 Emask