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I'm trying to write a code in which every 1 ms a number plused one , should be replaced the old number . (something like a chronometer ! ) .
the problem is whenever the cpu usage increases because of some other programs running on the pc, this 1 milliseconds is also increased and timing in my program changes !
is there any way to prevent cpu load changes affecting timing in my program ?
It sounds as though you are trying to generate an analogue output waveform with a digital-to-analogue converter card using software timing, where your software is responsible for determining what value should be output at any given time and updating the output accordingly.
This is OK for stationary or low-speed signals but you are trying to do it at 1 ms intervals, in other words to output 1000 samples per second or 1 ks/s. You cannot do this reliably on a desktop operating system - there are too many other processes going on which can use CPU time and block your program from running for many milliseconds (or even seconds, e.g. for network access).
Here are a few ways you could solve this:
Use buffered, hardware-clocked output if your analogue output device supports it. Instead of writing one sample at a time, you send the device a waveform or array of samples and it outputs them at regular intervals using a timing signal generated in hardware. Unfortunately, low-end DAQ devices often don't support hardware-clocked output.
Instead of expecting the loop that writes your samples to the AO to run every millisecond, read LabVIEW's Tick Count (ms) value in the loop and use that as an index to your array of samples: rather than trying to output every sample, your code will now say 'what time is it now, and therefore what should the output be?' That won't give you a perfect signal out but at least now it should keep the correct frequency rather than be 'slowed down' - instead you will see glitches imposed on the signal whenever the loop can't keep up. This is easy to test and maybe it will be adequate for your needs.
Use a real-time operating system instead of a desktop OS. In the case of LabVIEW this would mean using the Real-Time software module and either a National Instruments hardware device that supports RT, such as the CompactRIO series, or installing the RT OS on a dedicated PC if the hardware is compatible. This is not a cheap option, obviously (unless it's strictly for personal, home use). In any case you would need to have an RT-compatible driver for your output device.
Use your computer's sound output as the output device. LabVIEW has functions for buffered sound output and you should be able to get reliable results. You'll need to upsample your signal to one of the sound output's available sample rates, probably 44.1 ks/s. The drawbacks are that the output level is limited in range and is not calibrated, and will probably be AC-coupled so you can't output a DC or very low-frequency signal. However if the level is OK for what you want to connect it to, or you can add suitable signal conditioning, this could be a neat solution. If you need the output level to be calibrated you could simultaneously measure it with your DAQ card and scale the sound waveform you're outputting to keep it correct.
The answer to your question is "not on a desktop computer." This is why products like LabVIEW Real-Time and dedicated deterministic hardware exist: you need a computer built around dedication to a particular process in order to consistently serve that process. Every application in a regular Windows/Mac/Linux desktop system has the problem you are seeing of potentially being interrupted by other system processes, particularly in its UI layer.
There is no way to prevent cpu load changes from affecting timing in your program unless the computer has a realtime clock.
If it doesn't have a realtime clock, there is no reason to expect it to behave deterministically. Do you need for your program to run at that pace?
In my band, all musicians have both hands busy at any time. However, we want to add whole synthesizer chords (1/4 .. whole note length), maybe triggered by a simple foot switch every time (because playing along a sequencer is currently too difficult for us).
Some time ago I wrote a (Windows) console application in C (MinGW) that converted incoming MIDI events to text, piped that text to an external program (AWK script), and re-converted that external program's text output back to MIDI events.
Basically every sort of filtering or event generation was possible; I actually produced chords triggered by simple control messages; I kept note-ONs in memory to be able to -OFF them whenever a new chord was sent, etc. - the actual processing (execution) times were not a problem at all(!)
But I had to understand that not only latency, but also the notoriously unreliable (with respect to "when", "for how long") user application OS multitasking/switching made this concept practically worthless at least for "real-time" use. There were always clearly perceivable delays, of unpredictable duration.
I read about user-mode driver programming and downloaded some resources, but somehow stopped working on that project without a real result.
Apart from that specific project, I even have some experience in writing small "virtual" machines that allow for expressing exactly the variables, conditionals and math, stored as a token tree and processed quite fast. Maybe there is also the option to embed Lua, V8, or anything like that. So calling another (external) program is not necessarily the issue here, since that can be avoided.
The problem that remains is that the processing as a whole is still done by a (user) application. So I figure there is no way around a (user mode) driver, in this scenario.
Alternatively, I was even considering (more "real-time") hardware - a Raspi or the like - but then the MIDI interface may be an additional challenge.
Is there any hardware or software solution (or project) available that may serve as a base for such a _Generic MIDI filter/processor_? Apart from predictable timing behaviour, it is desirable not to need a (C) compilation environment when building filters/rules, since that "creative" step will probably happen in our rehearsal room (laptop available), which is certainly not a "programming lab". Text-based "programs" are fine - for long-term I'll maybe build a GUI for wiring/generating rules anyway.
MIDI is handled pretty well in Windows. I'm not sure the source of the original problems you had. No doubt there is some latency though.
You can handle this in real time with a microcontroller. The good news is that you don't even have to build the hardware. Off-the-shelf controllers are available for this. For example: http://www.midisolutions.com/prodevp.htm
having trouble understanding the exact role of an interpreter. to quote wikipedia - "Programs in interpreted languages[1] are not translated into machine code however, although their interpreter (which may be seen as an executor or processor) typically consists of directly executable machine code (generated from assembly and/or high level language source code)."
my doubt is about this statement - "interpreter (which may be seen as an executor or processor) typically consists of directly executable machine code" ? what does that mean? interpreter is supposed to be a program .How can it 'execute' code by itself ? they have re-stated this fact by saying " interpreter is different from language translators like compilers". Can anyone clarify please ? Also what is the difference (if any) between interpreted language and machine code ?
Compiler:
Transforms your code into binary machine code which can be directly executed by the CPU. Example: C, Fortran
Interpreter:
Is a program that executes the code written by the programmer without an additional step of transformation. Example: Bash scripts, Formulas in Excel
Actually it is not that easy any more. There are many concepts between these two pols. Java is compiled into an intermediate language that is then interpreted, just-in-time compilers compile small parts of interpreted code to speed them up.
"How can it 'execute' code by itself?" Take the Excel example. If you type a calculation into a cell, Excel somehow executes the code, right? But Excel does not compile the code and run it, but it parses it and executes in a general way. Excel has a sum function that in the end is executed on the processor as an add machine command, but there is a lot to do for Excel in between.
I will briefly describe an emulator to explain the main concept mentioned in the question.
Suppose I am using Mame, a video game emulator, and select the old classic arcade "Miss PacMan". Looking at the schematic or looking directly at a PCB inside an arcade video game, it is easy to find the processor : the zilog Z80, the only large chip with 40 pins. Now, if we get the technical data for that processor, we can find the binary encoding for each instruction it can execute. Basically, it get a 8-bit data (value ranging from 0 to 255) which tells the processor what to do. In the case of the emulator, it read the byte (the exact same bytes as would do the Z80 processor inside the original miss pac-man electronic board), determine what a Z80 would do and simulate the instruction.
Some classic video game may have use a x86 processor, similar to the one currently used in most PC. Even when selecting such a game in Mame, the emulator would still read the bytes as found in that game and interpret each one the way the x86 processor would do. In other words, the emulator would not take advantage of the fact that the PC and the emulated game are using a similar processor. It would perform the same steps to emulate any game no matter if the PC on which Mame is running share any similitude with the original game.
You are asking how an interpreter could execute code? The interpreter is a program (the interpreter is just a software, not a physical processor). The wording is effectively confusing. For this sentence to make sense, we would need all the following conditions:
1 - the program to interpret is already in binary, in a machine language that can be executed directly by the processor used in your PC
2 - the program location, the exact address used, is the same as the location that you can reserve in your PC
3 - any library and any I/O occupy the exact same address
When all these condition can be meet, the interpreter could just tell the processor on your PC to stop executing the code from the interpreter but instead, "jump" in the code of the program to be interpreted. Anyone could then say : it is not an interpreter, it is just a launcher.
Maybe such an interpreter which actually does not interpret but let your processor do the real job is still useful in the following way: it could let your processor perform some of the work, but request the generation of an exception when the code to be interpreted is executing some type of instruction. For example, let the code running, but generate a "general protection error" or "trap" or "exception" when trying to execute any of the variant of "IN" or "OUT". The interpreter would take note of the I/O port being written or it would choose a value to give instead of allowing to read a real I/O port. The interpreter would then manage to get the processor "jump" in the program to interpret at the location just after the instruction "IN" or "OUT".
Normally, an interpreter read an ASCII text file, the original source code (which could be Unicode instead of ASCII), determine line by line, word by word, what a compiler would do, then simulate the task on the fly. When the original compiler would need to read many lines to fully understand the current task, the interpreter would also need to read all these lines before being able to simulate the same task.
A big advantage of an interpreter is that it can not crash. Because every instruction is simulated, it is not sensitive to any bug or malicious code. That was a big advantage at the time when computers needed to reboot after encountering any bug, at a time where reboot was taking 10 minutes or more.
Today, with fast SSD to reboot in 5 second and with reliable operating systems which can trap any error in one process and close that process without affecting the stability of the machine, there is less incentive to prefer a slow interpreter over a much faster JIT or much much faster binary executable
It came to my attention some emulators and virtual machines use dynamic recompilation. How do they do that? In C i know how to call a function in ram using typecasting (although i never tried) but how does one read opcodes and generate code for it? Does the person need to have premade assembly chunks and copy/batch them together? is the assembly written in C? If so how do you find the length of the code? How do you account for system interrupts?
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system interrupts and how to (re)compile the data is what i am most interested in. Upon more research i heard of one person (no source available) used js, read the machine code, output js source and use eval to 'compile' the js source. Interesting.
It sounds like i MUST have knowledge of the target platform machine code to dynamically recompile
Yes, absolutely. That is why parts of the Java Virtual Machine must be rewritten (namely, the JIT) for every architecture.
When you write a virtual machine, you have a particular host-architecture in mind, and a particular guest-architecture. A portable VM is better called an emulator, since you would be emulating every instruction of the guest-architecture (guest-registers would be represented as host-variables, rather than host-registers).
When the guest- and host-architectures are the same, like VMWare, there are a ton of (pretty neat) optimizations you can do to speed up the virtualization - today we are at the point that this type of virtual machine is BARELY slower than running directly on the processor. Of course, it is extremely architecture-dependent - you would probably be better off rewriting most of VMWare from scratch than trying to port it.
It's quite possible - though obviously not trivial - to disassemble code from a memory pointer, optimize the code in some way, and then write back the optimized code - either to the original location or to a new location with a jump patched into the original location.
Of course, emulators and VMs don't have to RE-write, they can do this at load-time.
This is a wide open question, not sure where you want to go with it. Wikipedia covers the generic topic with a generic answer. The native code being emulated or virtualized is replaced with native code. The more the code is run the more is replaced.
I think you need to do a few things, first decide if you are talking about an emulation or a virtual machine like a vmware or virtualbox. An emulation the processor and hardware is emulated using software, so the next instruction is read by the emulator, the opcode pulled apart by code and you determine what to do with it. I have been doing some 6502 emulation and static binary translation which is dynamic recompilation but pre processed instead of real time. So your emulator may take a LDA #10, load a with immediate, the emulator sees the load A immediate instruction, knows it has to read the next byte which is the immediate the emulator has a variable in the code for the A register and puts the immediate value in that variable. Before completing the instruction the emulator needs to update the flags, in this case the Zero flag is clear the N flag is clear C and V are untouched. But what if the next instruction was a load X immediate? No big deal right? Well, the load x will also modify the z and n flags, so the next time you execute the load a instruction you may figure out that you dont have to compute the flags because they will be destroyed, it is dead code in the emulation. You can continue with this kind of thinking, say you see code that copies the x register to the a register then pushes the a register on the stack then copies the y register to the a register and pushes on the stack, you could replace that chunk with simply pushing the x and y registers on the stack. Or you may see a couple of add with carries chained together to perform a 16 bit add and store the result in adjacent memory locations. Basically looking for operations that the processor being emulated couldnt do but is easy to do in the emulation. Static binary translation which I suggest you look into before dynamic recompilation, performs this analysis and translation in a static manner, as in, before you run the code. Instead of emulating you translate the opcodes to C for example and remove as much dead code as you can (a nice feature is the C compiler can remove more dead code for you).
Once the concept of emulation and translation are understood then you can try to do it dynamically, it is certainly not trivial. I would suggest trying to again doing a static translation of a binary to the machine code of the target processor, which a good exercise. I wouldnt attempt dynamic run time optimizations until I had succeeded in performing them statically against a/the binary.
virtualization is a different story, you are talking about running the same processor on the same processor. So x86 on an x86 for example. the beauty here is that using non-old x86 processors, you can take the program being virtualized and run the actual opcodes on the actual processor, no emulation. You setup traps built into the processor to catch things, so loading values in AX and adding BX, etc these all happen at real time on the processor, when AX wants to read or write memory it depends on your trap mechanism if the addresses are within the virtual machines ram space, no traps, but lets say the program writes to an address which is the virtualized uart, you have the processor trap that then then vmware or whatever decodes that write and emulates it talking to a real serial port. That one instruction though wasnt realtime it took quite a while to execute. What you could do if you chose to is replace that instruction or set of instructions that write a value to the virtualized serial port and maybe have then write to a different address that could be the real serial port or some other location that is not going to cause a fault causing the vm manager to have to emulate the instruction. Or add some code in the virtual memory space that performs a write to the uart without a trap, and have that code instead branch to this uart write routine. The next time you hit that chunk of code it now runs at real time.
Another thing you can do is for example emulate and as you go translate to a virtual intermediate bytcode, like llvm's. From there you can translate from the intermediate machine to the native machine, eventually replacing large sections of program if not the whole thing. You still have to deal with the peripherals and I/O.
Here's an explaination of how they are doing dynamic recompilation for the 'Rubinius' Ruby interpteter:
http://www.engineyard.com/blog/2010/making-ruby-fast-the-rubinius-jit/
This approach is typically used by environments with an intermediate byte code representation (like Java, .net). The byte code contains enough "high level" structures (high level in terms of higher level than machine code) so that the VM can take chunks out of the byte code and replace it by a compiled memory block. The VM typically decide which part is getting compiled by counting how many times the code was already interpreted, since the compilation itself is a complex and time-consuming process. So it is usefull to only compile the parts which get executed many times.
but how does one read opcodes and generate code for it?
The scheme of the opcodes is defined by the specification of the VM, so the VM opens the program file, and interprets it according to the spec.
Does the person need to have premade assembly chunks and copy/batch them together? is the assembly written in C?
This process is an implementation detail of the VM, typically there is a compiler embedded, which is capable to transform the VM opcode stream into machine code.
How do you account for system interrupts?
Very simple: none. The code in the VM can't interact with real hardware. The VM interact with the OS, and transfer OS events to the code by jumping/calling specific parts inside the interpreted code. Every event in the code or from the OS must pass the VM.
Also hardware virtualization products can use some kind of JIT. A typical use cases in the X86 world is the translation of 16bit real mode code to 32 or 64bit protected mode code to not to be forced to emulate a CPU in real mode. Also a software-only VM replaces jump instructions in the executing code by jumps into the VM control software, which at each branch the following code path for jump instructions scans and them replace, before it jumps to the real code destination. But I doubt if the jump replacement qualifies as JIT compilation.
IIS does this by shadow copying: after compilation it copies assemblies to some temporary place and runs them from temp.
Imagine, that user change some files. Then IIS will recompile asseblies in next steps:
Recompile (all requests handled by old code)
Copies new assemblies (all requests handled by old code)
All new requests will be handled by new code, all requests - by old.
I hope this'd be helpful.
A virtual Machine loads "byte code" or "intermediate language" and not machine code therefore, I suppose, that it just recompiles the byte code more efficiently once it has more runtime data.
http://en.wikipedia.org/wiki/Just-in-time_compilation
I am somewhat familiar with the CUDA visual profiler and the occupancy spreadsheet, although I am probably not leveraging them as well as I could. Profiling & optimizing CUDA code is not like profiling & optimizing code that runs on a CPU. So I am hoping to learn from your experiences about how to get the most out of my code.
There was a post recently looking for the fastest possible code to identify self numbers, and I provided a CUDA implementation. I'm not satisfied that this code is as fast as it can be, but I'm at a loss as to figure out both what the right questions are and what tool I can get the answers from.
How do you identify ways to make your CUDA kernels perform faster?
If you're developing on Linux then the CUDA Visual Profiler gives you a whole load of information, knowing what to do with it can be a little tricky. On Windows you can also use the CUDA Visual Profiler, or (on Vista/7/2008) you can use Nexus which integrates nicely with Visual Studio and gives you combined host and GPU profile information.
Once you've got the data, you need to know how to interpret it. The Advanced CUDA C presentation from GTC has some useful tips. The main things to look out for are:
Optimal memory accesses: you need to know what you expect your code to do and then look for exceptions. So if you are always loading floats, and each thread loads a different float from an array, then you would expect to see only 64-byte loads (on current h/w). Any other loads are inefficient. The profiling information will probably improve in future h/w.
Minimise serialization: the "warp serialize" counter indicates that you have shared memory bank conflicts or constant serialization, the presentation goes into more detail and what to do about this as does the SDK (e.g. the reduction sample)
Overlap I/O and compute: this is where Nexus really shines (you can get the same info manually using cudaEvents), if you have a large amount of data transfer you want to overlap the compute and the I/O
Execution configuration: the occupancy calculator can help with this, but simple methods like commenting the compute to measure expected vs. measured bandwidth is really useful (and vice versa for compute throughput)
This is just a start, check out the GTC presentation and the other webinars on the NVIDIA website.
If you are using Windows... Check Nexus:
http://developer.nvidia.com/object/nexus.html
The CUDA profiler is rather crude and doesn't provide a lot of useful information. The only way to seriously micro-optimize your code (assuming you have already chosen the best possible algorithm) is to have a deep understanding of the GPU architecture, particularly with regard to using shared memory, external memory access patterns, register usage, thread occupancy, warps, etc.
Maybe you could post your kernel code here and get some feedback ?
The nVidia CUDA developer forum forum is also a good place to go for help with this kind of problem.
I hung back because I'm no CUDA expert, and the other answers are pretty good IF the code is already pretty near optimal. In my experience, that's a big IF, and there's no harm in verifying it.
To verify it, you need to find out if the code is for sure not doing anything it doesn't really have to do. Here are ways I can see to verify that:
Run the same code on the vanilla processor, and either take stackshots of it, or use a profiler such as Oprofile or RotateRight/Zoom that can give you equivalent information.
Running it on a CUDA processor, and doing the same thing, if possible.
What you're looking for are lines of code that have high occupancy on the call stack, as shown by the fraction of stack samples containing them. Those are your "bottlenecks". It does not take a very large number of samples to locate them.