Displaying 20 results from an estimated 202 matches for "vectorizeable".
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vectorizable
2011 May 22
0
[LLVMdev] No SSE instructions
On Sun, May 22, 2011 at 1:07 PM, Serg Anohovsky <serg.anohovsky at gmail.com>wrote:
> Hello.
> I have compiled the simple program:
>
> #include <stdio.h>
> #include <stdlib.h>
>
> int v1[10000];
>
> int main()
> {
> int i;
>
> for (i = 0; i < 10000; i++) {
> v1[i] = i;
> }
>
>
This loop
2012 Oct 16
4
[LLVMdev] Loop vectorizer
...e best vectorization factor
> (could be 1).
>
> 3. Legality check - This unit checks if it is *legal* (from a
> correctness point of view) to vectorize the program. This is target
> independent. Also, this unit needs to describe which transformation
> are needed to make this loop vectorizeable. For example: if-conversion
> is required if the control flow is not uniform for all iterations of
> the loop.
>
> 4. Vectorization - This is where the actual widening of the
> instructions happen. Every time we improve #3 by detecting more
> vectorizeable loops, we need to add t...
2012 Oct 16
2
[LLVMdev] Loop vectorizer
Nadav Rotem <nrotem at apple.com> wrote:
> I sent a patch to llvm-commit with a new loop vectorizer.
> This is a very simple loop vectorizer, but we have to start somewhere.
> With this new loop vectorizer we can already vectorize a good number of loops.
> I know that we can improve the new loop vectorizer in a number of ways.
> We can implement a precise dependence test,
>
2012 Oct 16
0
[LLVMdev] Loop vectorizer
...del - This unit decides on the best vectorization factor (could be 1).
3. Legality check - This unit checks if it is *legal* (from a correctness point of view) to vectorize the program. This is target independent. Also, this unit needs to describe which transformation are needed to make this loop vectorizeable. For example: if-conversion is required if the control flow is not uniform for all iterations of the loop.
4. Vectorization - This is where the actual widening of the instructions happen. Every time we improve #3 by detecting more vectorizeable loops, we need to add the mechanism for actually ge...
2015 Aug 13
2
[LLVMdev] Improving loop vectorizer support for loops with a volatile iteration variable
Hi Gerolf,
I think we have several (perhaps separable) issues here:
1. Do we have a canonical form for loops, preserved through the optimizer, that allows naturally-constructed loop nests to remain separable?
2. Do we forbid non-lowering transformations that turn vectorizable loops into non-vectorizable loops?
3. How do we detect cases where transformations cause a negative answer to either
2011 May 22
10
[LLVMdev] No SSE instructions
Hello.
I have compiled the simple program:
#include <stdio.h>
#include <stdlib.h>
int v1[10000];
int main()
{
int i;
for (i = 0; i < 10000; i++) {
v1[i] = i;
}
for (i = 0; i < 10000; i++) {
printf("%d ", v1[i]);
}
return 0;
}
Next, I disasseble the executable file and have not found
2017 Feb 27
2
[Proposal][RFC] Epilog loop vectorization
On 02/27/2017 12:41 PM, Michael Kuperstein wrote:
There's another issue with re-running the vectorizer (which I support, btw - I'm just saying there are more problems to solve on the way :-) )
Historically, we haven't even tried to evaluate the cost of the "constant" (not per-iteration) vectorization overhead - things like alias checks. Instead, we have hard bounds - we
2012 Oct 17
0
[LLVMdev] Loop vectorizer
...e best vectorization factor
> (could be 1).
>
> 3. Legality check - This unit checks if it is *legal* (from a
> correctness point of view) to vectorize the program. This is target
> independent. Also, this unit needs to describe which transformation
> are needed to make this loop vectorizeable. For example: if-conversion
> is required if the control flow is not uniform for all iterations of
> the loop.
>
> 4. Vectorization - This is where the actual widening of the
> instructions happen. Every time we improve #3 by detecting more
> vectorizeable loops, we need to add t...
2012 Oct 17
0
[LLVMdev] Loop vectorizer
Hi everybody,
On 10/17/12 12:32 AM, Hal Finkel wrote:
>>> Do you have a plan for xforms to increase the amount of
>>> vectorization?
>>
>> Yes. We will need to implement a predication phase and to design the
>> interaction with other loop transformations. Also, this will have to
>> work well with the cost model. We also need to think of a good way to
2005 Apr 22
1
RE: [R] when can we expect Prof Tierney's compiled R?
If we are on the subject of byte compilation, let me bring a couple of
examples which have been puzzling me for some time. I'd like to know a)
if the compilation will likely to improve the performance for this type
of computations, and b) at least roughly understand the reasons for the
observed numbers, specifically why x[i]<- assignment is so much slower
than x[i] extraction.
The loops
2013 Jun 06
2
[LLVMdev] Enabling the vectorizer for -Os
On Wed, Jun 5, 2013 at 5:51 PM, Nadav Rotem <nrotem at apple.com> wrote:
> Hi,
>
> Thanks for the feedback. I think that we agree that vectorization on -Os
> can benefit many programs. Regarding -O2 vs -O3, maybe we should set a
> higher cost threshold for O2 to increase the likelihood of improving the
> performance ? We have very few regressions on -O3 as is and with
2013 Jun 06
0
[LLVMdev] Enabling the vectorizer for -Os
Hi,
Thanks for the feedback. I think that we agree that vectorization on -Os can benefit many programs. Regarding -O2 vs -O3, maybe we should set a higher cost threshold for O2 to increase the likelihood of improving the performance ? We have very few regressions on -O3 as is and with better cost models I believe that we can bring them close to zero, so I am not sure if it can help that much.
2015 May 21
3
[LLVMdev] Alias-based Loop Versioning
There is a work taking place by multiple people in this area and more is expected to happen and I’d like to make sure we’re working toward a common end goal.
I tried to collect the use-cases for run-time memory checks and the specific memchecks required for each:
1. Loop Vectorizer: each memory access is checked against all other memory accesses in the loop (except read vs read)
2. Loop
2019 Sep 09
3
Vectorizing multiple exit loops
I've recently mentioned in a few places that I'm interested in enhancing
the loop vectorizer to handle multiple exit loops, and have been asked
to share plans. This email is intended to a) share my current thinking
and b) help spark discussion among interested parties. I do need to
warn that my near term plans for this have been delayed; I got pulled
into an internal project
2011 May 22
1
[LLVMdev] Fwd: No SSE instructions
---------- Forwarded message ----------
From: Serg Anohovsky <serg.anohovsky at gmail.com>
Date: 2011/5/22
Subject: Re: [LLVMdev] No SSE instructions
To: Chris Lattner <clattner at apple.com>
2011/5/22 Chris Lattner <clattner at apple.com>
>
> On May 22, 2011, at 10:47 AM, Justin Holewinski wrote:
>
> On Sun, May 22, 2011 at 1:07 PM, Serg Anohovsky
2015 Jan 12
8
[LLVMdev] RFC: Loop distribution/Partial vectorization
Hi,
We'd like to propose new Loop Distribution pass. The main motivation is to
allow partial vectorization of loops. One such example is the main loop of
456.hmmer in SpecINT_2006. The current version of the patch improves hmmer by
24% on ARM64 and 18% on X86.
The goal of the pass is to distribute a loop that can't be vectorized because of
memory dependence cycles. The pass splits
2013 Jun 05
15
[LLVMdev] Enabling the vectorizer for -Os
Hi,
I would like to start a discussion about enabling the loop vectorizer by default for -Os. The loop vectorizer can accelerate many workloads and enabling it for -Os and -O2 has obvious performance benefits. At the same time the loop vectorizer can increase the code size because of two reasons. First, to vectorize some loops we have to keep the original loop around in order to handle the last
2002 Oct 07
0
Why are big data.frames slow? What can I do to get it fas ter?
Extracting from data frame one element at a time the way you did is
expensive. I.e., test[i, 6] is slower than test$whatever[i].
As an example:
> dat <- data.frame(a = sample(LETTERS, 1e6, replace=TRUE), b=1:1e6,
+ c=rep("A", 1e6))
> dat$a <- as.character(dat$a)
> dat$c <- as.character(dat$c)
>
> system.time(
+ for(i in 1:10) {
+ dat[i, 3]
2015 Jul 16
4
[LLVMdev] Improving loop vectorizer support for loops with a volatile iteration variable
----- Original Message -----
> From: "Hal Finkel" <hfinkel at anl.gov>
> To: "Chandler Carruth" <chandlerc at google.com>
> Cc: llvmdev at cs.uiuc.edu
> Sent: Thursday, July 16, 2015 1:58:02 AM
> Subject: Re: [LLVMdev] Improving loop vectorizer support for loops
> with a volatile iteration variable
> ----- Original Message -----
> >
2005 Apr 27
1
RE: [R] when can we expect Prof Tierney's compiled R?
Luke,
Thank you for sharing the benchmark results. The improvement is very
substantial, I am looking forward to the release of the byte compiler!
The arithmetic shows that x[i]<- is still the bottleneck. I suspect that
this is due to a very involved dispatching/search for the appropriate
function on the C level. There might be significant gain if loops
somehow cached the result of the initial