search for: imperfectly

On 7/30/13 7:35 AM, Krzysztof Parzyszek wrote: > On 7/29/2013 6:28 PM, Andrew Trick wrote: >> >> You mean that LICM and Unswitching should be left for later? For the >> purpose of exposing scalar optimizations, I'm not sure I agree with >> that but I'd be interested in examples. > > Optimizations like LICM, and unswitching can potentially damage >

...epend on perfect loops. This concept really only makes sense for Source/AST level transformations anyway, which don't apply at the LLVM IR level. Some comments from an LNO such as Polly. In general, Polly and probably many modern loop nest optimizers do not care that much about perfectly or imperfectly nested loop nests. Transformations work either way. LICM is problematic due to another reason. LICM introduces new memory dependences. Here a simple example Normal loop: for i for j sum[i] += A[i][j] LICM loop: for i s = sum[i] for j s += A[i][j] sum[i] = s Calcu...

...concept really only makes sense for Source/AST >> level transformations anyway, which don't apply at the LLVM IR level. > > Some comments from an LNO such as Polly. In general, Polly and > probably many modern loop nest optimizers do not care that much about > perfectly or imperfectly nested loop nests. Transformations work > either way. > > LICM is problematic due to another reason. LICM introduces new memory > dependences. Here a simple example I'm pretty sure Open64's LNO is able to revert LICM-ed loop back to what to was. > > Normal loop: >...

On Jul 30, 2013, at 10:19 AM, Shuxin Yang <shuxin.llvm at gmail.com> wrote: > The pro for running LICM early is that it may move big redundant stuff out of loop nest. You never know > how big it is. In case you are lucky , you can move lot of stuff out of > loop, the loop may become much smaller and hence enable lots of downstream optimizations. This sound > to be a big win

Hi all! I'm new to this forum so please excuse me if I don't conform perfectly to the protocols on this board! I'm trying to get an estimate of true prevalence based upon results from an imperfect test. I have various estimates of se/sp which could inform my priors (at least upper and lower limits even if with a uniform distribution) and found the following code on this website..

I am using R to teach, and here are a couple of things that I thought would work didn't work. 1. I noticed the utility data(***,package=***) recently and like it very much, but unless I type in the whole word "package" I'll get an error in 1.4.0. For example, data(cats,package=MASS) works fine but data(cats,pac=MASS) doesn't. 2. drop1 doesn't seem to be as smart as

>> I'm talking about perfect loop nests, as in the classical fortran loop >> transformation sense. > > Most nest optimizations only apply to perfect nests. Each such > optimization could try to "fix" the nest for its own purposes, but it > would be a lot of duplicated effort. If each L.N.O pass have to fix by itself, I would say this LNO component is

On 7/31/2013 12:20 PM, Chris Lattner wrote: > On Jul 31, 2013, at 6:53 AM, Krzysztof Parzyszek > <kparzysz at codeaurora.org <mailto:kparzysz at codeaurora.org>> wrote: >> On 7/30/2013 11:44 PM, Chris Lattner wrote: >>> >>> The canonical form should be that loop invariants are hoisted. >> >> The canonical form should not depend on the knowledge

I have rails 1.0 and I cannot install rails-1.1 system-wide. However, I can freeze_edge (but just once because of svn 1.1.4 on Debian). Under this scenario, how can I create brand new rails-1.1 apps? I know how to freeze_edge *existing* rails-1.0 apps but that process seems to be imperfect because the script/about command and /rails/info/properties URL do not work after freezing to 1.1.0

...or >>> Source/AST level transformations anyway, which don't apply at the >>> LLVM IR level. >> >> Some comments from an LNO such as Polly. In general, Polly and >> probably many modern loop nest optimizers do not care that much about >> perfectly or imperfectly nested loop nests. Transformations work >> either way. >> >> LICM is problematic due to another reason. LICM introduces new memory >> dependences. Here a simple example > > I'm pretty sure Open64's LNO is able to revert LICM-ed loop back to > what to was....

I'm having some difficulty getting into Ogg. Being my first time encoding to Ogg, I am left doubtful of the quality in reproduction. Hopefully, it is merely something that I am doing. My original intentions were to go through my CD collection and rip everything out at 224kps VBR. I began with an album I was relatively familiar with. I used FreeRip 2.53 initially, but found that I had

I think all the common distros have pretty much stopped caring (if they ever did) about allowing users to reasonably operate their default environments with hardware that has imperfect 3D drivers. Please use environments that don't require 3D for regular operation on such boards. -ilia On Tue, May 30, 2017 at 7:36 PM, adlo <adloconwy at gmail.com> wrote: > In order to get a clear

On Tue, Jul 28, 2015 at 6:32 PM, Warren Young <wyml at etr-usa.com> wrote: > On Jul 28, 2015, at 4:37 PM, Nathan Duehr <denverpilot at me.com> wrote: >> Equating this to ?vaccination? is a huge stretch. > > Why? It's not just an imperfect analogy it really doesn't work on closer scrutiny. Malware itself is not a good analog to antigens. Vaccinations provide

Hi all, I have some probleem detecting DTMF send by a GSM phone, I'm using SIP with ulaw. do you know what are the options to improve the detection ? I'm using asterisk 1.05, is the CVS HEAD version had some improvement about DTMF detection? Florian.

Hi Ees, SCEV Delinearization is the closest I know. But it has its problems. Well for one your expression should be SCEVable. But more importantly, SCEV Delinearization is trying to deduce something that is high-level (actually source-level) from a low-level IR in which a lot of this info has been lost. So, since there's not a 1-1 mapping from high-level code to LLVM IR, going backwards will

On Thursday, March 13, 2014, Diego Novillo <dnovillo at google.com> wrote: > > On Mar 13, 2014 6:57 PM, "Bob Wilson" <bob.wilson at apple.com<javascript:_e(%7B%7D,'cvml','bob.wilson at apple.com');>> > wrote: > > > > > This is a proposal for the instrumentation-based approach that I talked > about at the dev meeting. I

Thank you, those links were indeed helpful. It appears to me that while JumpCloud.com touts it's Samba compatibility (including "Samba Schema support"), their's is an imperfect implementation. Because they do not leverage the Samba group objectclass they are hampering Samba's ability. The method they've used to implement groups does not allow those groups to be used by

On Mon, Nov 16, 2015 at 6:59 PM, Dmitri Gribenko via llvm-dev < llvm-dev at lists.llvm.org> wrote: > On Mon, Nov 16, 2015 at 10:03 AM, James Molloy via llvm-dev > <llvm-dev at lists.llvm.org> wrote: > > You don't appear to have addressed my suggestion to not require a perfect > > external world, instead to measure the overhead of an imperfect world (by > >

Hi Richard, You don't appear to have addressed my suggestion to not require a perfect external world, instead to measure the overhead of an imperfect world (by using an empty benchmark) and subtracting that from the measured benchmark score. Besides which, absolute benchmark results are more than often totally useless - the really important part of benchmarking is relative differences.

Michael makes a great point about aliasing here and different indexing that accesses the same element! Another note: x = A[0][2] is fundamentally different depending on the type of `A`. If e.g. A was declared: int A[10][20], there's only _one_ load. A is a (and is treated as) a linear buffer, and GEPs only pinpoint the specific position of A[0][2] in this buffer (i.e. 0*10 + 2). But if A was