Displaying 8 results from an estimated 8 matches for "pred0".
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2015 May 13
8
[LLVMdev] RFC: Convergent attribute
...e if-else construct.
Logically, the thread that wishes to execute the texture2D races with its
neighbor to reads the neighbor's value of r0 before it gets overridden.
In most SPMD/SIMT implementations, the fallout of this races is exposed via
the predicated expression of acyclic control flow:
pred0 <- cmp ...
if (pred0) r0 = ...
if (pred0) r2 = r0 + ...
if (!pred0) r1 = texture2D(..., r0, ...)
if (!pred0) r2 = r1 + ...
If thread 0 takes the else path and perform the texture2D operation, but
its neighbor thread 1 takes the then branch, then the texture2D will fail
because thread 1 has al...
2015 May 14
2
[LLVMdev] RFC: Convergent attribute
...to execute the texture2D races with its
>> neighbor to reads the neighbor's value of r0 before it gets overridden.
>>
>> In most SPMD/SIMT implementations, the fallout of this races is exposed via
>> the predicated expression of acyclic control flow:
>>
>> pred0 <- cmp ...
>> if (pred0) r0 = ...
>> if (pred0) r2 = r0 + ...
>> if (!pred0) r1 = texture2D(..., r0, ...)
>> if (!pred0) r2 = r1 + ...
>>
>> If thread 0 takes the else path and perform the texture2D operation, but
>> its neighbor thread 1 takes the th...
2015 Aug 14
2
[LLVMdev] RFC: Convergent attribute
..., the thread that wishes to execute the texture2D races with its
> neighbor to reads the neighbor's value of r0 before it gets overridden.
>
> In most SPMD/SIMT implementations, the fallout of this races is exposed via
> the predicated expression of acyclic control flow:
>
> pred0 <- cmp ...
> if (pred0) r0 = ...
> if (pred0) r2 = r0 + ...
> if (!pred0) r1 = texture2D(..., r0, ...)
> if (!pred0) r2 = r1 + ...
>
> If thread 0 takes the else path and perform the texture2D operation, but
> its neighbor thread 1 takes the then branch, then the texture2...
2015 Aug 14
2
[LLVMdev] RFC: Convergent attribute
...cute the texture2D races with its
>> neighbor to reads the neighbor's value of r0 before it gets overridden.
>>
>> In most SPMD/SIMT implementations, the fallout of this races is exposed
>> via
>> the predicated expression of acyclic control flow:
>>
>> pred0 <- cmp ...
>> if (pred0) r0 = ...
>> if (pred0) r2 = r0 + ...
>> if (!pred0) r1 = texture2D(..., r0, ...)
>> if (!pred0) r2 = r1 + ...
>>
>> If thread 0 takes the else path and perform the texture2D operation, but
>> its neighbor thread 1 takes the the...
2011 Aug 02
0
[LLVMdev] Multiple successors, single dynamic successor
...such relationships in LLVM IR ("best" in the sense of allowing
> other optimizations to run effectively)? Bear in mind that in this
> example N=2, but it may be way bigger than that.
Just to clarify: I already figured out two ways to do it, i.e.:
%0 = phi i8* [blockaddr(%succ0), %pred0], [blockaddr(%succ1), %pred1],
...
...
indirectbr %0, [%succ0, %succ1, ...]
or
%0 = phi i8 [0, %pred0], [1, %pred1], ...
...
switch %0, undef, [0, %succ0], [1, %succ1], ...
what I'd like to know is which one do you think is better (and why) or
if there are better ways I didn't think of...
2012 May 03
1
overlapping confidence bands for predicted probabilities from a logistic model
...a=data.frame(x=c(0,1)), se.fit=T)
with(pred, cbind(low = plogis(fit - 1.96*se.fit), est = plogis(fit), up = plogis(fit + 1.96*se.fit))) # confidence bands based on SEs
# simulation-based confidence bands:
sims <- t(replicate(200, coef(glm(simulate(mod1)$sim_1 ~ x, data=dat, family=binomial))))
pred0 <- plogis(quantile(sims%*%c(1,0), c(0.025, 0.5, 0.975)))
pred1 <- plogis(quantile(sims%*%c(1,1), c(0.025, 0.5, 0.975)))
rbind(pred0, pred1)
# the upper bound of the prediction for x=0 is greater than the lower bound of the prediction for x=1, using both methods
2011 Aug 02
3
[LLVMdev] Multiple successors, single dynamic successor
Nella citazione martedì 2 agosto 2011 20:02:08, Michael Ilseman ha
scritto:
> I'm assuming that you're talking about a situation where this can't be
> determined statically in the existing LLVM IR, but you know it's true
> and want to put it in (e.g. you're the one generating LLVM IR).
Correct. Or, more precisely, I'd like to investigate macro compression,
i.e.
2009 Apr 01
3
How to prevent inclusion of intercept in lme with interaction
...s=subject,data=grd,
type="l",xlim=c(0,20),ylim=c(0,3))
# With intercept
grd.lme1 = lme(newbone~t*treat,data=grd,random=~1|subject)
grd$pred1 = predict(grd.lme1,level=0)
summary(grd.lme1)
# How go force intercept = 0 ???
grd.lme0 = lme(newbone~t*treat-1,data=grd,random=~1|subject)
grd$pred0 = predict(grd.lme0,level=0)
summary(grd.lme0)
# Gives true,
all.equal(grd$pred1,grd$pred0)
# Everything as expected without treat
grd.lme2 = lme(newbone~t,data=grd,random=~1|subject)
grd$pred2 = predict(grd.lme2,level=0)
summary(grd.lme2)
# Forced intercept = 0
grd.lme3 = lme(newbone~t-1,data=grd...