similar to: LLVM Backend for a platform with no (normal) stack

Thanks for your response. Please see below. From: Bruce Hoult [mailto:brucehoult at sifive.com] Sent: Thursday, December 13, 2018 5:58 PM To: jjones at prc-hsv.com Cc: LLVM Developers Mailing List <llvm-dev at lists.llvm.org> Subject: Re: [llvm-dev] LLVM Backend for a platform with no (normal) stack Do you have a register that you can store a memory address >> yes in and

Thanks, no malloc or free equivalents either (no heap). So, there are no others (to your knowledge) who have built an LLVM backend for a platform with no “normal” stack? I found a presentation about some FPGA work (using LLVM) but it doesn’t seem to apply to my platform. Perhaps someone else on the mailing list will have come across this rarity? Thank you again for your time and

For a machine like an FPGA with no stack, you have to ensure that you have an optimization that rewrites the alloca into either registers (such as PromoteMem2Reg) or that you rewrite the alloca by declaring a static local, and rewriting the code to use that instead of the alloca result. Mark Mendell From: llvm-dev <llvm-dev-bounces at lists.llvm.org> On Behalf Of Bruce Hoult via llvm-dev

Yes, thank you, specifically and all. On this platform, we call what I will use a "frame stack" (it's actually not a stack, but that's really not relevant). Special thanks to Mr. Mendell--I promise to make good use of the contents of lib/Transforms/Utils/PromoteMemoryToRegister.cpp. To All, I'm sorry I wasn't clear in my original posting. In hindsight, it was clearly

Not only do FPGAs not support recursion, we don’t even support calls! All user code must be inlined into one kernel/component, which is then used to create HDL for the FPGA. Mark From: Bruce Hoult <brucehoult at sifive.com> Sent: December 17, 2018 9:28 AM To: Mendell, Mark P <mark.p.mendell at intel.com> Cc: jjones at prc-hsv.com; LLVM Developers Mailing List <llvm-dev at

If we're talking about member variables, just put an m in front of it, problem solved. You already have one for s_, and I didn't see you mention it but I assume you'd want g_ for globals, so m_ makes perfect sense for member variables and there's no question about UB at that point. On Mon, Feb 4, 2019 at 1:27 PM JD Jones via llvm-dev < llvm-dev at lists.llvm.org> wrote:

Hi Tim, Sorry, I'm not sure I follow. Are you maybe thinking that if the identifiers were tagged to specify scope, people would still be trying to use acronyms or single letters? So that, what in future code might be F, would instead be _f and that would be worse than f_ or s_f? I was thinking instead F would be (for new or modified code) _function or _fnctn or _func (as an object of type

On 2/4/2019 2:29 PM, Tim Northover via llvm-dev wrote: > On Mon, 4 Feb 2019 at 20:21, JD Jones <jjones at prc-hsv.com> wrote: >> If _<lowerCaseLetter> violates a standard, please say which one. It does not violate the C++11 standard: > > If strictly adhered to, it doesn't, and I've never claimed any > different. But coding standards are never strictly adhered

I so agree. I have found scope based coding conventions very useful. My favorite was: * Static data member: s_<lowerCaseLetterThenCamelCase> * Non-static data members: _<lowerCaseLetterThenCamelCase> (This was allowed by the C++ standard I last read. It’s _<UpperCase> that is reserved) * Function argments:

If _<lowerCaseLetter> violates a standard, please say which one. It does not violate the C++11 standard: •Reserved in any scope, including for use as implementation macros: •identifiers beginning with an underscore followed immediately by an uppercase letter •identifiers containing adjacent underscores (or "double underscore") •Reserved in the global namespace: •identifiers

I'm looking for someone to explain the difference between these procedures. The function prcomp() does principal components anaylsis, and the function cmdscale() does classical multi-dimensional scaling (also called principal coordinates analysis). My confusion stems from the fact that they give very similar results: my.d <- matrix(rnorm(50), ncol=5) rownames(my.d) <-

Dear List, I'm using gam in a multiple imputation framework -- specifying the knot locations, and saving the results of multiple models, each of which is fit with slightly different data (because some of it is predicted when missing). In MI, coefficients from multiple models are averaged, as are variance-covariance matrices. VCV's get an additional correction to account for how

I have the manual for S+ 6 and I'm trying to use R for the Principle Component Analysis example and I'm getting a few interesting answers... The log is as follows: R : Copyright 2001, The R Development Core Team Version 1.3.0 (2001-06-22) R is free software and comes with ABSOLUTELY NO WARRANTY. You are welcome to redistribute it under certain conditions. Type `license()' or

Good Morning, all, I stumbled across a couple o' three of curious things in the LLVM code. I'm too new to this to know whether these are functioning correctly or not. Guidance would be appreciated. Perhaps it is something I have done wrong, but my executions of llc are creating two FPPassManager objects (that run different sets of passes). FPPassManager contains a static char ID

Estimados Soy un nuevo usario de R, y estoy usando como base de datos el European Social Survey, que tiene datos de 40,000 individuos, y alrededor de 23 países europeos. Lo que he seleccionado es la útima ola, el round 7, para el año 2014. He leido los datos, desde SPSS y aquí tienen la base de datos y que tipo de objetos se han generado, y tambíen la distribución por pais de la muestra. No he

Gracias. Alguna idea de que usar para calcular los porcentajes y almacenarlos. Se puede usar flat table? El 18/06/2017 4:50 p. m., "Carlos J. Gil Bellosta" <cgb en datanalytics.com> escribió: > Los porcentajes que obtienes con tu código son sobre todas las facetas, no > país a país. > > Calcula los porcentajes previamente a por país y representa esa columna en >

I am using a "for" loop to read a table row by row and I have to specify how many records are there in the table. I need to read row by row because the table is huge and the memory not large enough for the whole table.: number.of.records=100 fp=file("abc.csv","r") pos=seek(fp, rw="read") for (i in 1:number.of.record){ current.row=scan(file=fp,

#Simple table con frecuencias absolutas y crear relativas count =table(ess$stflife) percent = 100* (count)/sum(count) Carlos he creado a esto a nivel general en vez de usar prop.table. Según lo que dices o entiendo, debo de usar la función ddply para hacerlo a nivel de todos los paises, y entiendo que ddply (, c(""), debo de indicar los paises? Saludos 2017-06-18 17:37 GMT-05:00

Creo que esto me da para DK, y luego veré como aplicar el barplot ess %>% filter(cntry %in% c("DK")) %>% count (stflife) %>% mutate (freq = (n /sum(n)*100))%>% print 2017-06-18 19:01 GMT-05:00 Antonio Rodriguez Andres < antoniorodriguezandres70 en gmail.com>: > He conseguido el total para un país, pero no me deja usar percent = > count() /sum(count),

I have an array called "stocks" which contains numeric dates, ticker symbols,prices, etc. > stocks[1:3,] DATE TICKER PERMNO EXCHCD TSYMBOL TRDSTAT SHROUT PRC RET 1 19950131 EWST 10001 3 EWST A 2224 -7.75000 -0.031250 2 19950228 EWST 10001 3 EWST A 2224 7.54688 -0.026210 3 19950331 EWST