similar to: DTRACE_PROBE2() how to use it in the device driver code

Is there any way to get printf type functionality inside the kernel from dtrace probes. Basically I want to dump progress through flow in my device driver. Something like: DTRACE_PRINTF("Inside chip reset, mailboxes %x %x %x %x %x %x %x %x", mb1, mb2, .....); ... ... DTRACE_PRINTF("reset failed: reason %s", failure_reasons[err]); I may have several such probes and they may

Hi Jean-Marc, Thanks a lot for reviewing this huge assembly function! silk_warped_autocorrelation_FIX_c()'s kernel part is for( n = 0; n < length; n++ ) { tmp1_QS = silk_LSHIFT32( (opus_int32)input[ n ], QS ); /* Loop over allpass sections */ for( i = 0; i < order; i++ ) { /* Output of allpass section */ tmp2_QS = silk_SMLAWB(

This is a great idea. But the order (psEncC->shapingLPCOrder) can be configured to 12, 14, 16, 20 and 24 according to complexity parameter. It's hard to get a universal function to handle all these orders efficiently. Any suggestions? Thanks, Linfeng On Mon, Feb 6, 2017 at 12:40 PM, Jean-Marc Valin <jmvalin at jmvalin.ca> wrote: > Hi Linfeng, > > On 06/02/17 02:51 PM,

Hi Jean-Marc, Thanks for your suggestions. Will get back to you once we have some updates. Linfeng On Mon, Feb 6, 2017 at 5:47 PM, Jean-Marc Valin <jmvalin at jmvalin.ca> wrote: > Hi Linfeng, > > On 06/02/17 07:18 PM, Linfeng Zhang wrote: > > This is a great idea. But the order (psEncC->shapingLPCOrder) can be > > configured to 12, 14, 16, 20 and 24 according to

Hi, Attached is a patch with arm neon optimizations for silk_warped_autocorrelation_FIX(). Please review. Thanks, Felicia -------------- next part -------------- An HTML attachment was scrubbed... URL: <http://lists.xiph.org/pipermail/opus/attachments/20170131/9a912bb4/attachment-0001.html> -------------- next part -------------- A non-text attachment was scrubbed... Name:

I attached a new patch with small cleanup (disassembly is identical as the last patch). We have done the same internal testing as usual. Also, attached 2 failed temporary versions which try to reduce code size (just for code review reference purpose). The new patch of silk_warped_autocorrelation_FIX_neon() has a code size of 3,228 bytes (with gcc). smaller_slower.c has a code size of 2,304

Hello R-friends, i have a question to the "text"-function. a little test-dataset for better understanding: -the dataset was imported with read.table(....,header=TRUE) s1-s10 are the samplenames var1 var2 var3 s1 1 1 2 s2 2 3 1 s3 2 2 3 s4 5 4 3 s5 4 2 3 s6 6 3 2 s7 8 5 4 s8 7 2 1 s9 9 3 2

Thank Jean-Marc! The speedup percentages are all relative to the entire encoder. Comparing to master, this optimization patch speeds up fixed-point SILK encoder on NEON as following: Complexity 5: 6.1% Complexity 6: 5.8% Complexity 8: 5.5% Complexity 10: 4.0% when testing on an Acer Chromebook, ARMv7 Processor rev 3 (v7l), CPU max MHz: 2116.5 Thanks, Linfeng On Wed, Apr 5, 2017 at 11:02 AM,

Hi, I am trying to read the "credit.lisp" file of the Japanese credit database in UCI repository, but it is in lisp format which I do not know how to read. I have not found how to do that in the foreign library http://archive.ics.uci.edu/ml/datasets/Japanese+Credit+Screening <http://archive.ics.uci.edu/ml/datasets/Japanese+Credit+Screening> Could anyone help me? Best

Hi, ABCRegister.td : def SGPR32 : RegisterClass<"ABC", [i32], 16, (add S0, S1, S2, S3, S4, S5, S6, S7, S8, S9, S10, S11, S12, S13, S14, S15 )>; def SFGPR32 : RegisterClass<"ABC", [f32], 16, (add S0, S1, S2, S3, S4, S5, S6, S7, S8, S9, S10, S11, S12, S13, S14, S15 )>; ===== Instruction selection ends: ... t8: i32 = ADDrr t37, t32

Dear R users, I have copied for following table from an article on "Using confidence intervals in within-subject designs": Subject 1sec 2sec 5sec 1 10 13 13 12.00 2 6 8 8 7.33 3 11 14 14 13.00 4 22 23 25 23.33 5 16 18 20 18.00 6 15 17 17 16.33 7 1 1 4 2.00 8 12 15 17 14.67 9 9 12 12 11.00 10 8 9 12 9.67 I rearranged the data this way:

I am confused when trying the function survfit. my question is: what does the survival curve given by plot.survfit mean? is it the survival curve with different covariates at different points? or just the baseline survival curve? for example, I run the following code and get the survival curve #### library(survival) fit<-coxph(Surv(futime,fustat)~resid.ds+rx+ecog.ps,data=ovarian)

Hi R-users, I have a question relating to the HoltWinters() function. I am trying to forecast a series using the Holt Winters methodology but I am getting some unusual results. I had previously been using R for Windows version 2.7.2 and have just started using R 2.9.1. While using version 2.7.2 I was getting reasonable results however upon changing versions I found I started to see unusual

Not sure why, but Vitelity changed the settings to IP based authentication on me. Here's the new sip.conf settings they sent me. type=friend dtmfmode=auto host=64.2.142.93 allow=all nat=yes canreinvite=no trustrpid=yes sendrpid=yes When I use these settings to originate calls using the sip.conf they sent me, everything works. Action: Originate ActionID: S8 Channel:

I don't know if this is the best place to post this question but I will try anyway. I have two experiements for which I use one-way matched-randomized ANOVA for the analysis and I would like to compare different treatments in the two experiments. The only common group in the two experiments are the controls. Is there any ANOVA design that allows me to make this comparison taking into

I have some data 'myData' in wide form (attached at the end), and would like to convert it to long form. I wish to have five variables in the result: 1) Subj: factor 2) Group: between-subjects factor (2 levels: s / w) 3) Reference: within-subject factor (2 levels: Me / She) 4) F: within-subject factor (2 levels: F1 / F2) 5) J: within-subject factor (2 levels: J1 / J2) As this is the

New architectures only define the renameat2() system call, which was added in Linux 3.15. Define rename() and renameat() as wrappers for it if necessary. Signed-off-by: Ben Hutchings <ben at decadent.org.uk> --- --- a/usr/klibc/Kbuild +++ b/usr/klibc/Kbuild @@ -59,7 +59,8 @@ klib-y += vsnprintf.o snprintf.o vsprint inet/inet_ntoa.o inet/inet_aton.o inet/inet_addr.o \

I am running 9 negative binomial regressions with count data. The nine models use 9 different dependent variables - items of a clinical screening instrument - and use the same set of 5 predictors. Goal is to find out whether these predictors have differential effects on the items. Due to various reasons, one being that I want to avoid overfitting models, I need to employ identical types of

Hi R User, I am new in R and trying to create tables with selecting rows randomly (but with replacement) for each group but each group should have same number as original. Is it possible to create it using the following example data set? Your help is highly appreciated. dat1<-structure(list(RegionA = structure(c(1L, 1L, 2L, 3L, 3L, 4L, 5L, 5L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L),

> >% gdiff ../kqemu-osol-1.3.0pre9/kqemu-solaris.c . > >54c54 > >< static uint_t kqemu_busy = 0; > >--- > > > > > >>static uint32_t kqemu_busy = 0; > >> > >> > >73c73 > >< static uint_t upages_locked = 0; > >--- > > > > > >>static uint32_t upages_locked = 0; > >> >