xmm | Trading Bot for Ripple Network | Cryptocurrency library
kandi X-RAY | xmm Summary
kandi X-RAY | xmm Summary
This package encapsulates RippleAPI, providing both CLI and API, and implements an automated multi-currency market maker for the Ripple network using the Talmud strategy.
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QUESTION
I usually hear the term vectorized functions in one of two ways:
- In a very high-level language when the data is passed all-at-once (or at least, in bulk chunks) to a lower-level library that does the calculations in faster way. An example of this would be python's use of
numpy
for array/LA-related stuff. - At the lowest level, when using a specific machine instruction or procedure that makes heavy use of them (such as YMM, ZMM, XMM register instructions).
However, it seems like the term is passed around quite generally, and I wanted to know if there's a third (or even more) ways in which it's used. And this would just be, for example, passing multiple values to a function rather than one (usually done via an array) for example:
...ANSWER
Answered 2021-Jun-10 at 20:43Vectorized code, in the context you seem to be referring to, normally means "an implementation that happens to make use of Single Instruction Multiple Data (SIMD) hardware instructions".
This can sometimes mean that someone manually wrote a version of a function that is equivalent to the canonical one, but happens to make use of SIMD. More often than not, it's something that the compiler does under the hood as part of its optimization passes.
In a very high-level language when the data is passed all-at-once (or at least, in bulk chunks) to a lower-level library that does the calculations in faster way. An example of this would be python's use of numpy for array/LA-related stuff.
That's simply not correct. The process of handing off a big chunk of data to some block of code that goes through it quickly is not vectorization in of itself.
You could say "Now that my code uses numpy, it's vectorized" and be sort of correct, but only transitively. A better way to put it would be "Now that my code uses numpy, it runs a lot faster because numpy is vectorized under the hood.". Importantly though, not all fast libraries to which big chunks of data are passed at once are vectorized.
...Code examples...
Since there is no SIMD instruction in sight in either example, then neither are vectorized yet. It might be true that the second version is more likely to lead to a vectorized program. If that's the case, then we'd say that the program is more vectorizable than the first. However, the program is not vectorized until the compiler makes it so.
QUESTION
Originally I was trying to reproduce the effect described in Agner Fog's microarchitecture guide section "Warm-up period for YMM and ZMM vector instructions" where it says that:
The processor turns off the upper parts of the vector execution units when it is not used, in order to save power. Instructions with 256-bit vectors have a throughput that is approximately 4.5 times slower than normal during an initial warm-up period of approximately 56,000 clock cycles or 14 μs.
I got the slowdown, although it seems like it was closer to ~2x instead of 4.5x. But what I've found is on my CPU (Intel i7-9750H Coffee Lake) the slowdown is not only affecting 256-bit operations, but also 128-bit vector ops and scalar floating point ops (and even N number of GPR-only instructions following XMM touching instruction).
Code of the benchmark program:
...ANSWER
Answered 2021-Apr-01 at 06:19The fact that you see throttling even for narrow SIMD instructions is a side-effect of a behavior I call implicit widening.
Basically, on modern Intel, if the upper 128-255 bits are dirty on any register in the range ymm0
to ymm15
, any SIMD instruction is internally widened to 256 bits, since the upper bits need to be zeroed and this requires the full 256-bit registers in the register file to be powered and probably the 256-bit ALU path as well. So the instruction acts for the purposes of AVX frequencies as if it was 256-bit wide.
Similarly, if bits 256 to 511 are dirty on any zmm register in the range zmm0
to zmm15
, operations are implicitly widened to 512 bits.
For the purposes of light vs heavy instructions, the widened instructions have the same type as they would if they were full width. That is, a 128-bit FMA which gets widened to 512 bits acts as "heavy AVX-512" even though only 128 bits of FMA is occurring.
This applies to all instructions which use the xmm/ymm registers, even scalar FP operations.
Note that this doesn't just apply to this throttling period: it means that if you have dirty uppers, a narrow SIMD instruction (or scalar FP) will cause a transition to the more conservative DVFS states just as a full-width instruction would do.
QUESTION
Issue : I have 7 images in a list (with different size, resolution and format). I am adding an mp3 audio file and fade effect while making a slideshow with them, as i am trying to do it by following command
...ANSWER
Answered 2021-Mar-17 at 17:49Remove -framerate 1/5
. That's too low of a value for your given -t
and it won't work well with fade (image a fade at 0.2 fps). You're only applying that to the first input, while the rest are using the default -framerate 25
. Remove it and the image will be visible.
Alternatively, use -framerate 1
for each image input, and add fps=25
after each setsar
. It will be significantly faster.
QUESTION
As I understand, since AVX, trough the 3-Byte VEX or EVEX prefix, you can encode up to 32 XMM/YMM/ZMM registers in 64-bit mode, but when looking trough the Intel manual past the fact that it tells you that is possible, I cannot find the part where it explains how that actually occurs. There is only one extension field that I can see, which is the REX inverted fields, but not anything else, aside from a special place in the EVEX prefix to encode mask registers.
You would need 2 bits somewhere to encode that many registers. Do you have to combine 2 of the inverted REX fields inside the VEX/EVEX prefixes somehow, or how does this process work?
...ANSWER
Answered 2021-Mar-14 at 10:58xmm16..31 (and their ymm/zmm equivalents) are new with AVX-512 and only accessible via EVEX prefixes, which have 2 extra bits to add to each of the ModRM fields, and a 5 more bits as an extra field for the third operand.
REX + legacy-SSE, and VEX for AVX1/2 encodings, can only access xmm/ymm0..15.
Wikipedia's EVEX article has a pretty good table that shows where the bits come from, which I transcribed some of:
Addr mode Bit 4 Bit 3 Bits [2:0] Register type REG EVEX.R' EVEX.R ModRM.reg General Purpose, Vector RM EVEX.X EVEX.B ModRM.r/m GPR, Vector NDS/NDD EVEX.V' EVEX.v3 EVEX.v2v1v0 Vector Base 0 EVEX.B SIB.base (or modrm) GPR Index 0 EVEX.X SIB.index GPRIf the R/M operand is a vector register instead of a memory addressing mode, it uses both the X (index) and B (base) bits as extra register-number bits. Because that means there's no SIB.index field which could also need extension to select r8..r15.
In REX and VEX prefixes, The X bit goes unused when the source operand isn't memory with an indexed addressing mode. (https://wiki.osdev.org/X86-64_Instruction_Encoding#REX_prefix, but note in a register-number table earlier in that page showing X.Reg, X is just a placeholder for R or B, not REX.X; confusing choice on that page).
See also x86 BSWAP instruction REX doesn't follow Intel specs? for another diagram of using an extra register-number bit from a REX prefix.
QUESTION
I am studying AVX-512. I have a question about VORPS.
The documentation says like this:
EVEX.512.0F.W0 56 /r VORPS zmm1 {k1}{z}, zmm2, zmm3/m512/m32bcst
Return the bitwise logical OR of packed single-precision floating-point values in zmm2 and zmm3/m512/m32bcst subject to writemask k1.
EVEX encoded versions: The first source operand is a ZMM/YMM/XMM register. The second source operand can be a ZMM/YMM/XMM register, a 512/256/128-bit memory location, or a 512/256/128-bit vector broadcasted from a 32-bit memory location. The destination operand is a ZMM/YMM/XMM register conditionally updated with writemask k1.
Ref: https://www.felixcloutier.com/x86/orps
What does "subject to writemask k1" mean?
Can anyone give a concrete example of k1 contribution in this instruction?
I wrote this code to do some experiment about VORPS: https://godbolt.org/z/fMcqoa
Code ...ANSWER
Answered 2021-Feb-27 at 04:16The reason of why mask register did not affect the result is because I did not encode the mask register in the destination operand for vorps
.
In AT&T syntax, the usage is something like:
QUESTION
I am adding video stream capture functionality to a Xamarin Forms project. I am trying to use VLC's LibVLCSharp.Forms (https://github.com/videolan/libvlcsharp) package and the Mobile ffmpeg Xamarin wrapper package, Laerdal.Xamarin.FFmpeg.* (https://github.com/Laerdal/Laerdal.Xamarin.FFmpeg.iOS). However, the internal ffmpeg library from VLC is conflicting with the ffmpeg wrapper and is built with different flags which exclude functionality that I need.
For native development, it looks like you can configure a preferred library with the OTHER_LDFLAGS
flag in the Pods-.debug.xcconfig
file but I don't see where to do that with Xamarin.Forms.
Source: https://github.com/tanersener/mobile-ffmpeg/wiki/Using-Multiple-FFmpeg-Implementations-In-The-Same-iOS-Application
How can I configure Xamarin iOS builds to prefer the mobile ffmpeg library over the VLC ffmpeg library? If I am able to use the mobile ffmpeg library, will it cause issues with VLC?
Here is a log message when I try to run commands with ffmpeg. As you can see, ffmpeg's internal library paths reference "vlc":
...ANSWER
Answered 2021-Feb-26 at 05:52The solution is in one of the link you shared
For native development, it looks like you can configure a preferred library with the OTHER_LDFLAGS flag in the Pods-.debug.xcconfig file but I don't see where to do that with Xamarin.Forms. Source: https://github.com/tanersener/mobile-ffmpeg/wiki/Using-Multiple-FFmpeg-Implementations-In-The-Same-iOS-Application
Xamarin.Forms is still native development, so you can do this the same way a Swift iOS developer would.
- You need to open your native iOS app project in XCode (not the shared project one).
- Create a xcconfig file. This guide looks good enough with screenshots to help you navigate XCode.
- A xcconfig look like this. You want to put the mobile-ffmpeg frameworks before the mobilevlckit one.
- Xamarin.iOS might require some framework as well, so before all this I'd build your app in verbosity diagnostics mode to see what the current
OTHER_LDFLAGS
value is.
QUESTION
I'm working on a script that can do a few quick calculations that I usually do by hand. The string below varies because it is an item description but the format comes in two types typically. I need a way of parsing out the xMM
from the rest of the script because it's what I need to the calculations and can get it from there. I've tried using partition and some different .split()
combinations but I'm not sure that I'm understanding the finer inner workings on how they function.
The bold numbers vary but the info I'm trying to parse will always be (*)*MM
. If that helps.
ANSWER
Answered 2020-Dec-09 at 11:13You could use the following regex
QUESTION
I want to truncate a floating-point number in one of the xmm
registers to a 64-bit register, as stated by the title. Below I am dividing 15.9 by 4.95. I'm printing this out and I see that result is correct (3.212121). However, when using cvtss2si
to truncate this, rdi
is becoming zero in some way. I have no idea why. Why does this not truncate properly when I am expecting 3 as a result? I am on macOS assembling with Clang.
ANSWER
Answered 2020-Nov-18 at 04:52ss
is scalar single precision. You're converting the low 32-bits of the double
's mantissa. As a binary32 bit-pattern, that represents a small number or exactly zero. Also, if you want to truncate instead of round to nearest, use the truncating conversion (an extra t
). cvttsd2si rdi, xmm0
https://www.felixcloutier.com/x86/cvttsd2si.
Of course, xmm registers are call-clobbered in x86-64 System V, so it makes no sense to read XMM0 right after printf returns.
QUESTION
All the four _mm256_broadcastb_epi8, _mm_broadcastw_epi16, _mm256_broadcastd_epi32 and _mm256_broadcastq_epi64
functions are intrinsics for VPBROADCASTB, VPBROADCASTW, VPBROADCASTD and VPBROADCASTQ instructions accordingly.
According Intel's documentation: "Intel® Advanced Vector Extensions Programming Reference",
those instructions may receive a 8-bit, 16-bit 32-bit, 64-bit memory location accordingly.
Page 5-230:
The source operand is 8-bit, 16-bit 32-bit, 64-bit memory location or the low 8-bit, 16-bit 32-bit, 64-bit data in an XMM register
However, the intrinsic API (of Intel, MSVS and gcc) for those instructions receives a __m128i parameter. Now if i have a variable of basic type, supposedly 'short', what is the most efficient and cross-platform way (At least between MSVS and gcc) to pass that variable to the according broadcast intrinsic (_mm_broadcastw_epi16 in case of short)?
For Example:
...ANSWER
Answered 2020-Nov-04 at 10:53There are already sequence/compound intrinsics which do exactly what you want:
QUESTION
I try to create a video with ffmpeg
and save it to the device with gallery_saver
package for Flutter.
The ffmpeg
command works well and the video is created. But GallerySaver
does not save it. As result I get no error, but a false
boolean for the success
argument.
This is the ffmpeg
output. Is this a valid video mp4 file?
ANSWER
Answered 2020-Sep-18 at 17:03Make the video and add the audio in the same command. You can loop the images so it makes a proper length in relation to the audio:
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