I setup Intel mpi for parallel processing between 2 node with AMD opteron processor 2378 2.4GHZ and 16 GB memory. but this problem occur when i launch ansys. before it i launched successfully between to node with Intel processors and not have a problem with it.how can i solve this?
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I have a 2019 MacBook Pro 16". It has an Intel Core i9, 8-core processor and an AMD Radeon Pro 5500M with 8 GB GPU RAM.
I have the laptop dual booting Mac OS 12.4 and Windows 11.
Running clinfo under Windows tells me essentially that the OpenCL support is version 2.0, and that the addressing is 64-bits, and the max allocatable memory is between 7-8 GB.
Running clinfo under Mac OS tells me that OpenCL support is version 1.2, that addressing is 32-bits little endian, and the max allocatable memory is about 2 GB.
I am guessing this means that any OpenCL code I run is then restricted to using 2GB because of the 32-bit addressing (I thought that limit was 4GB), but I am wondering a) is this true and b) if it is true, is there any way to enable OpenCL under Mac to use the full amount of GPU memory?
OpenCL support on macOS is not great and has not been updated/improved for almost a decade. It always maxes out at version 1.2 regardless of hardware.
I'm not sure how clinfo determines "max allocatable memory," but if this refers to CL_DEVICE_MAX_MEM_ALLOC_SIZE, this is not necessarily a hard limit and can be overly conservative at times. 32-bit addressing may introduce a hard limit though. I'd also experiment with allocating your memory as multiple buffers rather than one giant one.
For serious GPU programming on macOS, it's hard to recommend OpenCL these days - tooling and feature support on Apple's own Metal API is much better, but of course not source compatible with OpenCL and only available on Apple's own platforms. (OpenCL is now also explicitly deprecated on macOS.)
There is an AES instruction or a DRNG instruction of the Intel CPU.
I would like to know if there is such an instruction on the AMD CPU or similar command.
Or is there a web site where i can get information about this?
I have a Mac OS X with 8 GB 1600 MHz DDR3 RAM and when I start unreal engine it complaints about Low RAM and asks that for best performance I should have at least 8 GB of RAM.
I'm not sure why is this is case, is it possible that its getting a lower share of RAM or something similar?
The Unreal Editor version is 4.7.5
Edit: The processor is 2.3 GHz Intel Core i7, and is 64 bit.
Edit: The graphic processor is Intel Iris Pro 1024 MB.
Why would UE4 not be able to access all of your RAM? I do not consider that case very likely.
Also, I would not worry about the RAM usage of UE4 too much. I do a lot of work with the engine and it rarely uses more than 3GB of RAM. Just make sure that your system as a whole has enough RAM for the running processes to prevent swapping.
Anyway, the bottleneck in your system is probably the graphics processor, so if your engine runs too slowly you should reduce the performance setting inside the engine.
I have recently purchased a development board utilizing Samsung Exynos5422 application processor (Cortex™-A15 2.0Ghz quad core and Cortex™-A7 quad core CPUs). I have tried to extract the performance counters in android using perf v3.0.8; however, none of the counters outputs a value (They are all "not counted"). Does anyone know how to solve this issue?
(The kernel version is 3.10.9)
I wrote a program with xcode (using portaudio) on a MacBook Pro (Intel Core 2 Duo 2.66 GHz). The Release works without problem (clear audio streaming) and the CPU Usage Level is almost 90%.
The problem arises when i run the Release on a Mac Pro (Quad Core Intel Xeon 2.8 GHz). The audio stream, when there is a large amount of computation, isn't clear (there are little clicks) despite the use of the CPU is four times lower than the one of MacBook Pro.
I can not understand why this happens.
25% CPU usage in a 4 core system means one core is 100% loaded. Also, I assume the Xeons are Pentium4 Xeons, which have way worse CPU cores than the Core2Duo, even though the clock frequency is a bit higher...