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...writer.c @@ -43,12 +43,11 @@ /* Things should be fastest when this matches the machine word size */ /* WATCHOUT: if you change this you must also change the following #defines down to SWAP_BE_WORD_TO_HOST below to match */ -/* WATCHOUT: there are a few places where the code will not work unless bwword is >= 32 bits wide */ -typedef FLAC__uint32 bwword; +/* WATCHOUT: there are a few places where the code will not work unless uint32_t is >= 32 bits wide */ #define FLAC__BYTES_PER_WORD 4 #define FLAC__BITS_PER_WORD 32 #define FLAC__WORD_ALL_ONES ((FLAC__uint32)0xffffffff) -/* SWAP_BE_W...

Hi everyone, I'm happy to announce that I've implemented a Block I/O bandwidth controller. The controller is designed to be of use in a cgroup or virtual machine environment. The current approach is that the controller is implemented as a device-mapper driver. What's dm-band all about? ======================== Dm-band is an I/O bandwidth controller implemented as a device-mapper

Hi everyone, I'm happy to announce that I've implemented a Block I/O bandwidth controller. The controller is designed to be of use in a cgroup or virtual machine environment. The current approach is that the controller is implemented as a device-mapper driver. What's dm-band all about? ======================== Dm-band is an I/O bandwidth controller implemented as a device-mapper

...l driver in use: virtio-pci -------------- next part -------------- randrw: (g=0): rw=randrw, bs=4K-4K/4K-4K, ioengine=libaio, iodepth=64 ... randrw: (g=0): rw=randrw, bs=4K-4K/4K-4K, ioengine=libaio, iodepth=64 Starting 8 processes randrw: (groupid=0, jobs=1): err= 0: pid=7155 read : io=384MB, bw=62,934KB/s, iops=15,733, runt= 6243msec slat (usec): min=4, max=11,681, avg=167.00, stdev=448.35 clat (usec): min=3, max=19,552, avg=2217.48, stdev=1367.27 bw (KB/s) : min= 0, max=70143, per=1.27%, avg=6362.85, stdev=19236.22 write: io=128MB, bw=21,046KB/s, iops=5,261, runt= 6243...

...l driver in use: virtio-pci -------------- next part -------------- randrw: (g=0): rw=randrw, bs=4K-4K/4K-4K, ioengine=libaio, iodepth=64 ... randrw: (g=0): rw=randrw, bs=4K-4K/4K-4K, ioengine=libaio, iodepth=64 Starting 8 processes randrw: (groupid=0, jobs=1): err= 0: pid=7155 read : io=384MB, bw=62,934KB/s, iops=15,733, runt= 6243msec slat (usec): min=4, max=11,681, avg=167.00, stdev=448.35 clat (usec): min=3, max=19,552, avg=2217.48, stdev=1367.27 bw (KB/s) : min= 0, max=70143, per=1.27%, avg=6362.85, stdev=19236.22 write: io=128MB, bw=21,046KB/s, iops=5,261, runt= 6243...

Benchmark shows small performance improvement on fusion io device. Before: seq-read : io=1,024MB, bw=19,982KB/s, iops=39,964, runt= 52475msec seq-write: io=1,024MB, bw=20,321KB/s, iops=40,641, runt= 51601msec rnd-read : io=1,024MB, bw=15,404KB/s, iops=30,808, runt= 68070msec rnd-write: io=1,024MB, bw=14,776KB/s, iops=29,552, runt= 70963msec After: seq-read : io=1,024MB, bw=20,343KB/s, iop...

Benchmark shows small performance improvement on fusion io device. Before: seq-read : io=1,024MB, bw=19,982KB/s, iops=39,964, runt= 52475msec seq-write: io=1,024MB, bw=20,321KB/s, iops=40,641, runt= 51601msec rnd-read : io=1,024MB, bw=15,404KB/s, iops=30,808, runt= 68070msec rnd-write: io=1,024MB, bw=14,776KB/s, iops=29,552, runt= 70963msec After: seq-read : io=1,024MB, bw=20,343KB/s, iop...

...distributions governed by a power law ... y ~ mu*x**lambda # In one of its forms # (can't find Pareto in the online help) Looking at the following should show my problem.... x3 <- runif(10000)**3 # Probably a better (correct) way to do this plot( density(x3,cut=0,bw=0.1)) plot( density(x3,cut=0,bw=0.01)) plot( density(x3,cut=0,bw=0.001)) plot(density(x3,cut=0,bw=0.1), log='xy') plot(density(x3,cut=0,bw=0.01), log='xy') plot(density(x3,cut=0,bw=0.001),log='xy') The upper three plots show that the bw has a big effect on the appearance...

...llonuridae/Data by genus/~Corbre/Corbre_2.txt",header=T,sep="\t",quote="")* *# create and calculate a new variable for time between call pusles * *Corbre_2 [c("TBC")] <- recode.variables(Corbre_2[c("TBC")] , "0 -> NA;")* *# Create new BW variable for band width then change data file name* *BW<-within(Corbre_2,BW<-Fmax-Fmin)* *# Create 2 new variables for fundamental H1 and third harmonic H3 frequencies * *#based on Fc that is generally loudest at the 2^nd harmonic.* *BW<-within(BW,FcH1<-Fc*.5)* *BW<-within(BW,F...

...f(!is.null(ylevels)) y <- factor(y, levels = if(is.numeric(ylevels)) levels(y)[ylevels] else ylevels) @@ -79,10 +80,12 @@ if(is.null(yaxlabels)) yaxlabels <- levels(y) ## unconditional density of x - dx <- if(is.null(from) & is.null(to)) - stats::density(x, bw = bw, n = n, ...) - else - stats::density(x, bw = bw, from = from, to = to, n = n, ...) + xnum <- as.numeric(x) + dx <- if (is.null(from) & is.null(to)) { + stats::density(xnum, bw = bw, n = n, ...) + } else { + stats::density(xnum, bw = bw, from = from, t...

...month 12 day 22 svn rev 57956 language R version.string R version 2.14.1 (2011-12-22) I just few days back started using R for basic statistical analysis. I want to plot the graph of following information > df disk vmfs vmdk IOPS BW 1 naa.5000a7203007ed8f 3 eager 16886.77 65.96393 2 naa.5000a7203007ed8f 3 lazy 44623.15 174.3092 3 naa.5000a7203007ed8f 5 eager 16767.53 65.49815 4 naa.5000a7203007ed8f 5 lazy 45891.55 179.2639 > str(df) 'data.frame': 4 obs. of 5 variables: $ disk:List of 4 ..$ : ch...

...erent methods for bandwidth determination. Below are the different ways in R on deciding the bandwidth. Can anyone give an idea on which ones are preferred. Also, how can I take a look at the source code for the density function? Thank you very much. Hannah x <- rnorm(1000) > bw.nrd(x) [1] 0.2688588 > bw.nrd0(x) [1] 0.2282763 > bw.ucv(x) [1] 0.2112366 > bw.bcv(x) [1] 0.2890085 Warning message: In bw.bcv(x) : minimum occurred at one end of the range > bw.SJ(x) [1] 0.2716242 > density(x, give.Rkern=T, kernel="gaussian") [1] 0.2820948 &g...

...=30 [code]: http://addictedtor.free.fr/graphiques/sources/source_30.R to my case but I do not obtain success. Somebody could give a tip to me, please? I am thankful anticipatedly. Cleber Borges #My code test ############## library(scatterplot3d) x=c(0.4, -1.2, .8, -.7, 0) d1 = density(x[1],bw=1.2, from=-3.0, to=3.0 ) d2 = density(x[2],bw=0.8, from=-3.0, to=3.0 ) d3 = density(x[3],bw=0.6, from=-2.5, to=2.5 ) d4 = density(x[4],bw=0.5, from=-2.0, to=2.0 ) d5 = density(x[5],bw=0.3, from=-1.5, to=1.5 ) sx = c(d1$x,d2$x,d3$x,d4$x,d5$x) sy = c(d1$y,d2$y,d3$y,d4$y,d5$y) sz = c(rep(0....

Dear R-help-list, The following is R function I wrote for computing multi-dimensional kernel density. I am seeking R experts who can make the code to run faster, 50 times faster ideally. Specifically, for function kernel.estimate = function(points, bw), the argument points is a d by n matrix as the n points in the d-dimensional space, bw is the bandwidth. The function will compute the kernel density estimate at the n-points of the input matrix points. To avoid the n^2 computational burden, I build a rd-tree which allows to quickly determine if...

...events are the milestones items in my project on milestones in the history of data visualization [1], and I want to compare trends in Europe vs. North America. I decided to use a graph of two overlaid density estimates with rug plots, but then the question arises of how to choose the bandwidth (BW) for the two series to allow them to be sensibly compared, because the range of time and total frequency differ for the two series. To avoid clutter on this list, I've placed the data and R code at http://euclid.psych.yorku.ca/SCS/Gallery/milestone/Test/kde-bug/mileyears4.R I have two vers...

...bject that has all of the variables (including the class variable)? (I am using the kohonen package, and in general I am using the SOM technique as a comparison to some other methods). I don't know if providing some or all data is useful, please let me know if you think it is. # get the data bw <- read.csv("bw.csv") # some missing values in data bwm <- data.frame(na.approx(bw, na.rm=FALSE, rule=2)) bw10 <- bwm[, 1:10] bw10.sc <- scale(bw10) bw.som <- som(data=bw10.sc, grid=somgrid(25,20,'hexagonal')) # playing with diff grid sizes # the different plots o...

I wanted to post my new shaping rules which I am running on my IPCOP router. They seem to be working very well so far. Any comments to my setup would be appreciated. #!/bin/bash # clear out the chain and setup a new chain iptables -t mangle -D OUTPUT -o eth1 -j BW-OUT 2> /dev/null > /dev/null iptables -t mangle -F BW-OUT 2> /dev/null > /dev/null iptables -t mangle -X BW-OUT 2> /dev/null > /dev/null iptables -t mangle -N BW-OUT iptables -t mangle -I POSTROUTING -o eth1 -j BW-OUT # mark packets: 2 is active ftp and passive ftp, 1 is ACK for d...

...priority classes - or you don''t use priorities - then excess bandwidth is distributed according to ratios of classes'' rates Am I right? Is there another way to influence distribution of excess bandwidth among siblings? E.g. is it possible to say that class A will acquire excess bw say 4 times faster than class B, even though class A''s rate is just half of class B''s rate? Thanks, pvl

...; provided initial performance data that indicates this optimization is worthwhile at high iops. Asias He <asias at redhat.com> reports the following fio results: Host: Linux 3.4.0+ #302 SMP x86_64 GNU/Linux Guest: same as host kernel Average 3 runs: with locked kick read iops=119907.50 bw=59954.00 runt=35018.50 io=2048.00 write iops=217187.00 bw=108594.00 runt=19312.00 io=2048.00 read iops=33948.00 bw=16974.50 runt=186820.50 io=3095.70 write iops=35014.00 bw=17507.50 runt=181151.00 io=3095.70 clat (usec) max=3484.10 avg=121085.38 stdev=174416.11 min=0.00 clat (usec) m...

...; provided initial performance data that indicates this optimization is worthwhile at high iops. Asias He <asias at redhat.com> reports the following fio results: Host: Linux 3.4.0+ #302 SMP x86_64 GNU/Linux Guest: same as host kernel Average 3 runs: with locked kick read iops=119907.50 bw=59954.00 runt=35018.50 io=2048.00 write iops=217187.00 bw=108594.00 runt=19312.00 io=2048.00 read iops=33948.00 bw=16974.50 runt=186820.50 io=3095.70 write iops=35014.00 bw=17507.50 runt=181151.00 io=3095.70 clat (usec) max=3484.10 avg=121085.38 stdev=174416.11 min=0.00 clat (usec) m...