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Apple Opencl Programming Guide For Mac

Book Description: Using the new OpenCL (Open Computing Language) standard, you can write applications that access all available programming resources: CPUs, GPUs, and other processors such as DSPs and the Cell/B.E. Already implemented by Apple, AMD, Intel, IBM, NVIDIA, and other leaders, OpenCL has outstanding potential for PCs, servers, handheld/embedded devices, high performance computing, and even cloud systems. This is the first comprehensive, authoritative, and practical guide to OpenCL 1.1 specifically for working developers and software architects.

Apple Opencl Programming Guide For Mac

Well, no, not really. But you don't want it to. First of all, let me say yet again, that 'GeForce Boost', or running the 9400M and 9600M GT as an SLI pair is NOT supported in hardware. This is because the 9600M GT would have to scale down so much to match the 9400M, the resulting performance would be worse than the 9600M GT by itself.

Ok, first, the pure awesome news: OpenCL really and truly does support both cards at the same time. More specifically, it sees them both as two entirely distinct devices, alongside the CPU. This is actually better than an SLI pair, as the software is free to decide which chip it wants to put to work for it's particular task. What follows is my own tests, from some tools posted over at the Mac Pro board.

You can get them here: (note that oclinfo requires registration at InsanelyMac for download. If someone has another link to it, or wants to start a torrent, post it here. That's ok to do, oclinfo is released under the GNU GPL) To install, unzip them and copy the executable file to your /usr/bin folder. (Use Finder's 'Go to Folder' to get there, it will not appear normally. You will be prompted for your admin password). To run, simply open Terminal, type the name of the program and hit Enter. Code: 1 OpenCL platform found!

Platform 0 Name: Apple Vendor: Apple Version: OpenCL 1.0 (Jul 15 2009 23:07:32) Profile: FULLPROFILE OpenCL-only Context 3 OpenCL devices found! Logitech webcam c930e software for mac download. OpenCL Bench V 0.25 by mitch.

Apple opencl programming guide for mac download

C2D 3GHz = 12 sec vs Nvidia 9600GT = 0,93 sec. Time results are not comparable to older version!. Number of OpenCL devices found: 3 OpenCL Device # 0 = GeForce 9600M GT Device 0 is an: GPU with max.

1250 MHz and 32 units/cores Now computing - please be patient. Time used: 2.805 seconds OpenCL Device # 1 = GeForce 9400M Device 1 is an: GPU with max.

1100 MHz and 16 units/cores Now computing - please be patient. Time used: 3.081 seconds OpenCL Device # 2 = Intel(R) Core(TM)2 Duo CPU P8600 @ 2.40GHz Device 2 is an: CPU with max. 2400 MHz and 2 units/cores Now computing - please be patient. Time used: 15.459 seconds Now checking if results are valid - please be patient.:) Validate test passed - GPU results=CPU results:) NOTE: When posting your results, PLEASE enclose it with the. Code: tags, to make it easier to read! As you can see here, the CPU, 9600M, and 9400M are ALL listed as devices!

The two GPUs are available simultaneously, and the benchmark uses them one after the other. You will also notice, however, that when the device check is performed looking for combined OpenGL/OpenCL devices, the 9400 does not appear. As per usual, it is not available as an OpenGL device when the 9600 is running, and one more time.NEVER WILL BE. (I get sick of seeing Hybrid SLI threads here, if you couldn't tell.) OK! Without further ado, let's get to benchmarking! Please post results from older (non-unibody) MacBook Pro's as well, and even other Apple laptops! Also, sidenote: See how the 9600M GT is listed as 1.25Ghz?

Meaning it isn't underclocked like some claim, at least not in it's max power state. It likely only underclocks at idle, or when running on battery. OpenCL Bench V 0.25 by mitch.

C2D 3GHz = 12 sec vs Nvidia 9600GT = 0,93 sec. Time results are not comparable to older version!. Number of OpenCL devices found: 2 OpenCL Device # 0 = GeForce 8600M GT Device 0 is an: GPU with max.

For

940 MHz and 32 units/cores Now computing - please be patient. Time used: 3.005 seconds OpenCL Device # 1 = Intel(R) Core(TM)2 Duo CPU T9300 @ 2.50GHz Device 1 is an: CPU with max. 2500 MHz and 2 units/cores Now computing - please be patient.

Time used: 15.304 seconds Now checking if results are valid - please be patient.:) Validate test passed - GPU results=CPU results:). Code: Last login: Sun Aug 30 16:34:57 on ttys000 Rheza-Pahlevis-MacBook-Pro: Rheza$ oclinfo 1 OpenCL platform found! Platform 0 Name: Apple Vendor: Apple Version: OpenCL 1.0 (Jul 15 2009 23:07:32) Profile: FULLPROFILE OpenCL-only Context 3 OpenCL devices found! Code: Last login: Sun Aug 30 17:25:53 on ttys000 Rheza-Pahlevis-MacBook-Pro: Rheza$ opencl.

OpenCL Bench V 0.25 by mitch. C2D 3GHz = 12 sec vs Nvidia 9600GT = 0,93 sec. Time results are not comparable to older version!. Number of OpenCL devices found: 3 OpenCL Device # 0 = GeForce 9600M GT Device 0 is an: GPU with max. 1250 MHz and 32 units/cores Now computing - please be patient. Time used: 2.794 seconds OpenCL Device # 1 = GeForce 9400M Device 1 is an: GPU with max. 1100 MHz and 16 units/cores Now computing - please be patient.

Time used: 9.037 seconds OpenCL Device # 2 = Intel(R) Core(TM)2 Duo CPU P8600 @ 2.40GHz Device 2 is an: CPU with max. 2400 MHz and 2 units/cores Now computing - please be patient. Time used: 18.394 seconds Now checking if results are valid - please be patient.:) Validate test passed - GPU results=CPU results:) Rheza-Pahlevis-MacBook-Pro: Rheza$. OpenCL Bench V 0.25 by mitch. C2D 3GHz = 12 sec vs Nvidia 9600GT = 0,93 sec.

Time results are not comparable to older version!. Number of OpenCL devices found: 2 OpenCL Device # 0 = GeForce 8600M GT Device 0 is an: GPU with max. 940 MHz and 32 units/cores Now computing - please be patient. Time used: 2.930 seconds OpenCL Device # 1 = Intel(R) Core(TM)2 Duo CPU T7700 @ 2.40GHz Device 1 is an: CPU with max.

2400 MHz and 2 units/cores Now computing - please be patient. Time used: 15.164 seconds Now checking if results are valid - please be patient.:) Validate test passed - GPU results=CPU results:). OpenCL Bench V 0.25 by mitch. C2D 3GHz = 12 sec vs Nvidia 9600GT = 0,93 sec. Time results are not comparable to older version!. Number of OpenCL devices found: 2 OpenCL Device # 0 = GeForce 9400M Device 0 is an: GPU with max. 1100 MHz and 16 units/cores Now computing - please be patient.

Time used: 3.510 seconds OpenCL Device # 1 = Intel(R) Core(TM)2 Duo CPU P8600 @ 2.40GHz Device 1 is an: CPU with max. 2400 MHz and 2 units/cores Now computing - please be patient. Time used: 15.853 seconds Now checking if results are valid - please be patient.:) Validate test passed - GPU results=CPU results:) logout Process completed. OpenCL Bench V 0.25 by mitch. C2D 3GHz = 12 sec vs Nvidia 9600GT = 0,93 sec.

Time results are not comparable to older version!. Number of OpenCL devices found: 3 OpenCL Device # 0 = GeForce 9600M GT Device 0 is an: GPU with max. 1250 MHz and 32 units/cores Now computing - please be patient. Time used: 2.794 seconds OpenCL Device # 1 = GeForce 9400M Device 1 is an: GPU with max. 1100 MHz and 16 units/cores Now computing - please be patient. Time used: 2.996 seconds OpenCL Device # 2 = Intel(R) Core(TM)2 Duo CPU T9800 @ 2.93GHz Device 2 is an: CPU with max. 2930 MHz and 2 units/cores Now computing - please be patient.

Apple Opencl Programming Guide For Mac Mac

Time used: 13.932 seconds Now checking if results are valid - please be patient.:) Validate test passed - GPU results=CPU results:) logout Process completed. From Apple's page on Concurrency and Application Design. The following Apple paragraphs seem a little contradictory, but this statement sums it up, '.any tasks that interact with the system are generally not recommended for use with OpenCL,' in the second paragraph. (relevant portion from Apple page follows) OpenCL and Concurrency The Open Computing Language (OpenCL) is a standards-based technology for performing general-purpose computations on a computer’s graphics processor. OpenCL is a good technology to use if you have a well-defined set of computations that you want to apply to large data sets. For example, you might use OpenCL to perform filter computations on the pixels of an image or use it to perform complex math calculations on several values at once. In other words, OpenCL is geared more toward problem sets whose data can be operated on in parallel.

Although OpenCL is good for performing massively data-parallel operations, it is not suitable for more general-purpose calculations. There is a nontrivial amount of effort required to prepare and transfer both the data and the required work kernel to a graphics card so that it can be operated on by a GPU. Similarly, there is a nontrivial amount of effort required to retrieve any results generated by OpenCL. As a result, any tasks that interact with the system are generally not recommended for use with OpenCL.

For example, you would not use OpenCL to process data from files or network streams. Instead, the work you perform using OpenCL must be much more self-contained so that it can be transferred to the graphics processor and computed independently. For more information about OpenCL and how you use it, see OpenCL Programming Guide for Mac OS X. OpenCL Bench V 0.25 by mitch.

C2D 3GHz = 12 sec vs Nvidia 9600GT = 0,93 sec. Time results are not comparable to older version!. Number of OpenCL devices found: 2 OpenCL Device # 0 = GeForce 8800 GT Device 0 is an: GPU with max. 1500 MHz and 112 units/cores Now computing - please be patient. Time used: 0.692 seconds OpenCL Device # 1 = Intel(R) Xeon(R) CPU E5462 @ 2.80GHz Device 1 is an: CPU with max. 2800 MHz and 8 units/cores Now computing - please be patient. Time used: 3.198 seconds Now checking if results are valid - please be patient.:) Validate test passed - GPU results=CPU results:)I can't believe Mac Pros are so fast compared to MacBooks.

Apple Opencl Programming Guide For Mac Os X

OpenCL Bench V 0.25 by mitch. C2D 3GHz = 12 sec vs Nvidia 9600GT = 0,93 sec.

Time results are not comparable to older version!. Number of OpenCL devices found: 3 OpenCL Device # 0 = GeForce 9600M GT Device 0 is an: GPU with max. 1250 MHz and 32 units/cores Now computing - please be patient. Time used: 15.626 seconds OpenCL Device # 1 = GeForce 9400M Device 1 is an: GPU with max. 1100 MHz and 16 units/cores Now computing - please be patient. Time used: 6.835 seconds OpenCL Device # 2 = Intel(R) Core(TM)2 Duo CPU T9550 @ 2.66GHz Device 2 is an: CPU with max. 2660 MHz and 2 units/cores Now computing - please be patient.

Time used: 17.362 seconds Now checking if results are valid - please be patient.:) Validate test passed - GPU results=CPU results:). OpenCL Bench V 0.25 by mitch. C2D 3GHz = 12 sec vs Nvidia 9600GT = 0,93 sec. Time results are not comparable to older version!. Number of OpenCL devices found: 3 OpenCL Device # 0 = GeForce 9600M GT Device 0 is an: GPU with max. 1250 MHz and 32 units/cores Now computing - please be patient.

Time used: 15.626 seconds OpenCL Device # 1 = GeForce 9400M Device 1 is an: GPU with max. 1100 MHz and 16 units/cores Now computing - please be patient. Time used: 6.835 seconds OpenCL Device # 2 = Intel(R) Core(TM)2 Duo CPU T9550 @ 2.66GHz Device 2 is an: CPU with max. 2660 MHz and 2 units/cores Now computing - please be patient. Time used: 17.362 seconds Now checking if results are valid - please be patient.:) Validate test passed - GPU results=CPU results:). QJulia OpenCL GPU FPS Bench 10.6 ONLY!

OPENCL - Good to know: - OpenCL is an API for universal GPU(CPU) computing - main difference to CUDA / ATI STEAM is: both only working with their 'own' gpu. An CUDA (NV) app like badaboom(h264 on GPU) cant work on an ATI gpu and vice versa - OpenCL is universal for different gpu vendors means: - Xcode / GCC compiles an code which includes the source (in C as an string) for the gpu programm that c source is, different to CUDA/ATI STEAM, is compiled later by OpenCL Framework at runtime! So same App can run on complete different gpus and also, without/less codechange om CPU if no OpemCL gpu (newer ones) is found The source (example below) for the gpu programm will be really compiled at runtime, not only interpreted. So little differences between run of my bench may happen because of that compile on the run wink.gif Does only GPU FPS, not CPU like the other benches here. I am not sure if the Apple code can handle more than one GPU. Source from Apple, minimal cosmetic changes (bigger window 800x800 vs 500x500 Apple = more GPU work) compiled with LLVM GCC 4.2 Now, an really complex qJulia number qrunching on GPU with OpenGL view of the result & FPS.

Other than Galaxy or OpenCL Bench, it now has an external opencl source file (.cl). That code (looks C code!) will be compiled by OpenCL framework at runtime and executed on GPU (really much gpu work!). In OpenCL apps you can include such source (as source strings) or, as with this example use an external.cl.

My 9600GT gets around 29 FPS in the startsquence (changes each start a bit), with Animation (key SPACE) from 16 - 60 FPS. 9600 GT / 29 FPS (16 - 60 FPS) MacBook Pro 13', GPU GeForce 9400M running at 6,25 fps (6-6,50) heavy load OpenCL work is possible on such mobilesOpenCL gpus / low end OpenCL gpus but not usefull Beside the gpu speed itself, such OpenCL parts need much own/real VRAM - if to less much VRAM-main memory swapping over PCIe. OpenCL Bench V 0.25 by mitch. C2D 3GHz = 12 sec vs Nvidia 9600GT = 0,93 sec. Time results are not comparable to older version!.

Number of OpenCL devices found: 3 OpenCL Device # 0 = GeForce 9600M GT Device 0 is an: GPU with max. 1250 MHz and 32 units/cores Now computing - please be patient. Time used: 2.787 seconds OpenCL Device # 1 = GeForce 9400M Device 1 is an: GPU with max. 1100 MHz and 16 units/cores Now computing - please be patient. Time used: 15.235 seconds OpenCL Device # 2 = Intel(R) Core(TM)2 Duo CPU T9400 @ 2.53GHz Device 2 is an: CPU with max.

2530 MHz and 2 units/cores Now computing - please be patient. Time used: 14.470 seconds Now checking if results are valid - please be patient.:) Validate test passed - GPU results=CPU results:) Is it just me or is my GeForce 9400M slow:blink.