openacc | Introduction to OpenACC | Learning library
kandi X-RAY | openacc Summary
kandi X-RAY | openacc Summary
This repository containes the exercises and other course material used in CSC's GPU Programming with OpenACC courses. The exercises and instructions for running them are described in this document.
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QUESTION
Is there a faster alternative for computing the argmin in OpenACC, than splitting the work in a minimum-reduction loop and another loop to actually find the index of the minimum?
This looks very wasteful:
...ANSWER
Answered 2021-Jun-10 at 16:53We've gotten requests for minloc/maxloc but it's difficult and would most likely not be performant, so not something that's been added. The method you're using is the recommended solution for this.
QUESTION
I currently have a makefile that is coded to compile OpenACC and I was wondering if I can make it support .cu as well
My current makefle:
...ANSWER
Answered 2021-May-13 at 14:17Please find below code by which you can use in the same makefile which will compile all files (.c and .cu) .
QUESTION
I am new to OpenACC and I am writing a new program from scratch (I have a fairly good idea what loops will be computationally costly from working in a similar problem before). I am getting an "Undefined reference" from nvlink. From my research, I found this is because no device code is being generated for the class I created. However, I don't understand why this is happening and how to fix it.
Below I send a MWE from my code.
include/vec1.h
...ANSWER
Answered 2021-May-10 at 15:52The problem here is that you're trying to call a device routine, "Vec1::operator*", that's contained in a shared object from a kernel in the main program. nvc++'s OpenACC implementation uses CUDA to target NVIDIA devices. Since CUDA doesn't have a dynamic linker for device code, at least not yet, this isn't supported.
You'll need to either link this statically, or move the "parallel loop" into the shared object.
Note that the "-ta" flag has been deprecated. Please consider using "-acc -gpu=cuda11.2" instead.
QUESTION
I'm working on a Bank assignment that is supposed to output a menu and allow user input to select what they want to do. The program is to loop and receive user input until the user enters "Q" for quit. After I loop once, there is an error message popping up saying java.util.NoSuchElementException.
Here is my code:
Bank.java
...ANSWER
Answered 2021-Apr-09 at 06:46The problem is that you close the scanner in the openAcc method. You should close only at the quitting from the program.
QUESTION
One MPI code, I am trying to parallelize a simple loop of it with openacc,and the output is not expected. Here, the loop has a call and I add a 'acc routine seq' in the subroutine. If I manually make this call inline and delete the subroutine, the result will be right. Do I use the OpenACC "routine" directive correctly? or other wrong?
- Runtime environment
MPI version: openmpi4.0.5
HPC SDK 20.11
CUDA Version: 10.2
ANSWER
Answered 2021-Apr-06 at 16:02The problem is with "i" being passed by reference (default with Fortran). Simplest solution is to pass it by value:
QUESTION
I'm using the pgc++ compiler on some C++ code that uses OpenACC directives, and I was wondering if there is a compiler option to disable implicit pragma generation that is performed when compiling code if the user leaves the required pragmas out. For example, when compiling my own code with the -Minfo=accel flag, I see the following messages appear:
ANSWER
Answered 2021-Jan-04 at 17:52This is the default behavior as defined by the OpenACC standard when a user does not use data clauses on a compute construct (parallel/kernels). A runtime check is performed and if the data is already present on the device, no action is performed. If the data is not on the device, then the data is copied.
You can add these variables to data clauses individually, or add a "default(present)" clause to your compute construct so all shared data will presumed to be present on the device. If the data is not present, then a runtime error will occur.
QUESTION
I have a GPU code that, at each iteration, decides if the iteration can be offloaded to the accelerator. OpenACC come to be the best tool:
...ANSWER
Answered 2020-Dec-19 at 03:03See section "3.2.6 acc get property" section of the OpenACC standard. In particular the "acc_property_free_memory" property.
https://www.openacc.org/sites/default/files/inline-images/Specification/OpenACC-3.1-final.pdf
QUESTION
Recent developments in gpus (the past few generations) allow them to be programmed. Languages like Cuda, openCL, openACC are specific to this hardware. In addition, certain games allow programming shaders which function in the rendering of images in the graphics pipeline. Just as code intended for a cpu can cause unintended execution resulting a vulnerability, I wonder if a game or other code intended for a gpu can result in a vulnerability.
...ANSWER
Answered 2020-Dec-17 at 00:41The benefit a hacker would get from targeting the GPU is "free" computing power without having to deal with the energy cost. The only practical scenario here is crypto-miner viruses, see this article for example. I don't know details on how they operate, but the idea is to use the GPU to mine crypto-currencies in the background, since GPUs are much more efficient than CPUs at this. These viruses will cause substential energy consumption if unnoticed.
Regarding an application running on the GPU causing/using a vulnerability, the use-cases here are rather limited since security-relevant data usually is not processed on GPUs. At most you could deliberately make the graphics driver crash and this way sabotage other programs from being properly executed. There already are plenty security mechanisms prohibiting reading other processes' VRAM etc., but there always is some way around.
QUESTION
I am trying to wrap my head around combining openacc with pointers to structs containing dynamically allocated members. The code below fails with
Failing in Thread:1 call to cuStreamSynchronize returned error 700: Illegal address during kernel execution
when compiled using nvc ("nvc 20.9-0 LLVM 64-bit target on x86-64 Linux -tp haswell"). As far as I can tell I am following the approach suggested eg in the OpenACC 'getting started' guide. But somehow presumably the pointers don't stick (?) on the device. Does anyone know what goes wrong here?
...ANSWER
Answered 2020-Dec-09 at 22:59From the compiler feedback messages you'll see something like:
QUESTION
I am trying to compile a basic openacc program in C, using gcc-10. It works fine for one-dimensional arrays, and arrays allocated through "A[N_x][N_y]" but when trying a 2D array allocated using malloc, either contiguous or not, I get an error message upon compiling. The example below fails:
...ANSWER
Answered 2020-Dec-07 at 18:44The code is fine, but I don't believe GNU supports non-contiguous data segments. I'll need to defer the GNU folks but do believe that they are developing this support in future versions of the compilers.
For now, you'll need to either switch to using the NVIDIA HPC Compiler (https://developer.nvidia.com/hpc-sdk) or refactor the code to use a single dimension array of size N_x*N_y with a computed index. Something like:
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