similar to: How to fit Oggs in a specific amount of space?

From: Jyri Sarha <jsarha at ti.com> I optimized Speex resampler for NEON capable ARM CPUs. The first patch should speed up resampling on any platform that can spare the increased memory usage. It would be nice to have these merged to the master branch. Please let me know if there is anything I can do to help the the merge. The patches have been rebased on top of master branch in

Hi I was surprised with size of Theora files and thought of feedback. Following 1minute duration Theora and Xvid files were made from a y4m file. The resolution is 1280x720: 1. Xvid 17MB 2. Ogg/Theora Q7 31MB 3. Ogg/Theora Q8 38MB 4. Ogg/Theora Q9 49MB 5. Ogg/Theora Q10 61MB The Xvid file was made using mencoder by 2 passes with following options:

I currently have a data frame whose rows correspond to each student and whose columns are different variables for the student, as shown below: Lastname Firstname CATALOG_NBR Email StudentID EMPLID Start 1 alastname afirstname 1213 *@uark.edu 10295236 # 12/2/2008 2 anotherlastname anotherfirstname 1213 **@uark.edu ## 10295236 9/3/2008 Xattempts Q1

On 21 September 2012 09:28, Sebastien DELDON-GNB <sebastien.deldon at st.com> wrote: > declare <16 x float> @llvm.arm.neon.vmaxs.v16f32(<16 x float>, <16 x float>) nounwind readnone > > llc fails with following message: > > SplitVectorResult #0: 0x2258350: v16f32 = llvm.arm.neon.vmaxs 0x2258250, 0x2258050, 0x2258150 [ORD=3] [ID=0] > > LLVM ERROR: Do not

On 14 October 2013 19:31, Arnold Schwaighofer <aschwaighofer at apple.com>wrote: > Renato, can you post the c code for the function and the assembly that gcc > produces? > Attached. Your initial example could be well handled by vectorization of strided > loops (and the mentioning of VLD3(.8?)/VST3(.8?) lead me to assume that > this is what happened). But the LLVM-IR you

Hi all, I would like to know if LLVM Neon intrinsics are designed to support only 'Legal' types for NEON units. Using llc -march=arm -mcpu=cortex-a9 vmax4.ll -o vmax4.s on following ll code: ; ModuleID = 'vmax.ll' target datalayout = "e-p:32:32:32-i1:8:8-i8:8:8-i16:16:16-i32:32:32-i64:64:64-f32:32:32-f64:64:64-v64:64:64-v128:128:128-a0:0:64-n32" target triple =

This is my first post to R-help and I look forward receiving some advice for a novice like me... I?ve got a simple repeated (4 periods so far) 10-question survey data that is very easy to work on Excel. However, I?d like to move the compilation to R but I?m having some trouble operating on count list data in a neat way. The data C > str(C) 'data.frame': 551 obs. of 13

I'm looking for a way to improve code that's proven to be inefficient. Suppose that a data source generates the following table every minute: Index Count ------------ 0 234 1 120 7 11 30 1 I save the tables in the following CSV format: time,index,count 0,0:1:7:30,234:120:11:1 1,0:2:3:19,199:110:87:9 That is, each line represents a table, and I

Renato, can you post the c code for the function and the assembly that gcc produces? Your initial example could be well handled by vectorization of strided loops (and the mentioning of VLD3(.8?)/VST3(.8?) lead me to assume that this is what happened). But the LLVM-IR you sent has a store of 0 in there ;) and strides by 4. Thanks, Arnold Vectorization of strided loops: I am using float as the

I have end of semester teaching evaluation data of the following form: > head(evaluations) Course Prefix Q1 Q2 Q3 Q4 Q5 Q6 Q7 Q8 Q9 Q10 Q11 Q12 Q13 Q14 1 2330301 2 4 3 3 3 4 4 1 2 5 4 1 1 1 1 2 2330301 2 3 3 3 3 3 5 1 2 5 8 1 1 1 1 3 2330301 2 4 4 3 3 4 4 2 2 5 9 1 1 1 1 4 2330301 2 2 1 1 3 4 5 1 2 5 8

Hello R users! I have several data frames where some of the variables have many missing observations. For example, Q1 in one of my data frames has over 66% of its observations missing. I have tried imputation with mice but it does not work for all the data frames and I get the following message or a similar message to this: iter imp variable 1 1 Q1 Q2 Q3 Q4 Q5 Q6 Q7 Q8 Q9 Q10 Q11

Hi all, Yes, it's true. A new version of rehuff, the tool that losslessly compresses Vorbis files: one that is easy to compile, and that works with newer-than-two-years-ago streams, too! On 1.0 streams, you get about 3% size reduction, and the headers get _much_ smaller (which helps for fast-start network streams). Building it should be easy (you might have to add some -I and -L for

Hi all, Yes, it's true. A new version of rehuff, the tool that losslessly compresses Vorbis files: one that is easy to compile, and that works with newer-than-two-years-ago streams, too! On 1.0 streams, you get about 3% size reduction, and the headers get _much_ smaller (which helps for fast-start network streams). Building it should be easy (you might have to add some -I and -L for

Hullo, folks. As the wiki is *still* down, I'm sending this to the list again. The EZAV EMP-400 is a small flash-based portable player with an OLED screen. I think it's still in development, because I can't find information on its pricing anywhere. The memory capacity isn't visible anywhere either, but the previous device from EZAV had 256 megs of memory.

This is almost ideal for SLP vectorization, except for two problems: 1. We have 4 stores to consecutive locations, but the last element is the constant zero, and not an additional SUB. At the moment we don’t have support for idempotence operations, but this is something that we should add. 2. The values that we are subtracting come from 3 loads. We usually load 4 elements from memory, or

Hiya, Here is the sources to my "rehuff" program. ./rehuff in.ogg out.ogg does a lossless recoding of a vorbis stream. (It generates optimal huffman codes for the particular stream). This code is meant for developers only, until someone is kind enough to provide good build and configure support for it. I won't. And no installation help questions please. There is a little patch

R Experts, I have a dataframe made up of character vectors--these are results from survey questions. I need to convert them to factors. I tried the following which did not work: scs2<-sapply(scs2,as.factor) also this didn't work: scs2<-sapply(scs2,function(x) as.factor(x)) After doing either of above I end up with >str(scs2) chr [1:10, 1:10] "very important" "very

Hi: How do I select different variables from a list of data frames. I have a list of 13 that looks like below. Each data frame has more variables than I need. How do I go through the list and select the variables that I need. In the example below, I need to get the variables "a", and "q10" and "q14" to be returned to two separate data frames. Thank you. Yours, Simon

Hi. I have been working on a tool whose goal is to reduce the bit rate of theora video by decoding to DCT coefficients, reducing the entropy of the coefficients, and re-tokenizing the stream. I have successfully used the decoder source to extract the DCT coefficients for each block, and I am able to capture any and all relevant information about where the block of coefficients falls in the

I was up late last night, and i had a thought on peeling that would probably provide 100% accurate peeling data to a decoder, but take a maximum of 1101 times normal time to encode (taking into account the range from q-1 to q10 ). ay you want to encode a track at q10, but you want it to be peelable. the 1101 encoder would encode from the source at every quantifiable level (since there are 2