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2009-11-10, 06:06
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#45 |
Jul 2009
Tokyo
2·5·61 Posts |
Hi,
New version on GTX260. This version use Matrix transpose with Cuda(see NVIDIA_GPU_Computing_SDK/C/src/transpose). This version support only 4096k. MacLucasFFTW.cuda.t.tar.gz $ time ./MacLucasFFTW 216091 Iteration 10000 M( 216091 )C, 0x30247786758b8792, n = 4194304, MacLucasFFTW v8.1 Ballester ... Iteration 210000 M( 216091 )C, 0xcfe091c8f59f8a7b, n = 4194304, MacLucasFFTW v8.1 Ballester M( 216091 )P, n = 4194304, MacLucasFFTW v8.1 Ballester real 99m5.087s user 42m45.096s sys 0m0.272s $ time ./MacLucasFFTW 63333333 Iteration 10000 M( 63333333 )C, 0xa5d7a917d728239a, n = 4194304, MacLucasFFTW v8.1 Ballester M( 63333333 )C, 0xa5d7a917d728239a, n = 4194304, MacLucasFFTW v8.1 Ballester real 4m20.656s user 1m41.750s sys 0m0.112s 4096k fft sec/iter = 0.026 Thank you, |
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2009-11-10, 07:15
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#46 |
Jul 2003
So Cal
1010011001112 Posts |
I just retested the 4096K FFT for the recent versions on the C1060. Version k is the fastest.
Version k: 0.0264 sec/iter Version o: 0.0278 sec/iter Version t: 0.0324 sec/iter |
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2009-11-10, 07:45
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#47 | |
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Jul 2009
Tokyo
2×5×61 Posts |
Hi, frmky
Quote:
Arguments 63333333 Max.Execution Time:30 Thank you, |
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2009-11-10, 08:15
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#48 |
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Jul 2003
So Cal
2,663 Posts |
Attached is the csv. I'll upload the graph in the next post.
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2009-11-10, 08:16
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#49 |
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Jul 2003
So Cal
2,663 Posts |
Here's the graph:
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2009-11-10, 08:46
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#50 | |
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Jul 2009
Tokyo
61010 Posts |
Quote:
transpose_kernel copt from NVIDIA_GPU_Computing_SDK/C/src/transpose/transpose_kernel.cu ,I don't touch. mmm... |
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2009-11-10, 09:17
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#51 |
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Jul 2003
So Cal
2,663 Posts |
Not sure if it'll help, but...
Code:
[childers release]$ ./transpose Transposing a 256 by 4096 matrix of floats... Naive transpose average time: 2.286 ms Optimized transpose average time: 0.327 ms Test PASSED Press ENTER to exit... |
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2009-11-10, 09:25
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#52 |
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Jul 2009
Tokyo
2×5×61 Posts |
Code:
$ ./transpose Transposing a 256 by 4096 matrix of floats... Naive transpose average time: 1.281 ms Optimized transpose average time: 0.184 ms |
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2009-11-10, 09:58
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#53 |
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Jul 2003
So Cal
1010011001112 Posts |
Try using transposeDiagonal from transposeNew.cu.
Code:
[TransposeNew] > Device 0: "Tesla C1060" > SM Capability 1.3 detected: > CUDA device has 30 Multi-Processors > SM performance scaling factor = 1.00 Matrix size: 2048x2048 (64x64 tiles), tile size: 32x32, block size: 32x8 Kernel Loop over kernel Loop within kernel ------ ---------------- ------------------ simple copy 73.02 GB/s 74.76 GB/s shared memory copy 70.46 GB/s 71.84 GB/s naive transpose 2.13 GB/s 2.14 GB/s coalesced transpose 17.53 GB/s 18.25 GB/s no bank conflict trans 17.70 GB/s 18.34 GB/s coarse-grained 17.70 GB/s 18.33 GB/s fine-grained 69.51 GB/s 72.12 GB/s diagonal transpose 63.91 GB/s 69.27 GB/s Test PASSED Press ENTER to exit... |
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2009-11-10, 15:03
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#54 | |
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Jul 2009
Tokyo
2·5·61 Posts |
Quote:
Only support 2048k,4096k. $ time ./MacLucasFFTW 216091 Iteration 10000 M( 216091 )C, 0x30247786758b8792, n = 2097152, MacLucasFFTW v8.1 Ballester ... Iteration 210000 M( 216091 )C, 0xcfe091c8f59f8a7b, n = 2097152, MacLucasFFTW v8.1 Ballester M( 216091 )P, n = 2097152, MacLucasFFTW v8.1 Ballester real 48m8.792s user 0m22.289s sys 0m9.177s $ time ./MacLucasFFTW 33333333 Iteration 10000 M( 33333333 )C, 0xd717246f501c7d94, n = 2097152, MacLucasFFTW v8.1 Ballester M( 33333333 )C, 0xd717246f501c7d94, n = 2097152, MacLucasFFTW v8.1 Ballester real 2m9.478s user 0m1.248s sys 0m0.528s 2048k fft sec/iter = 0.0130 $ time ./MacLucasFFTW 63333333 Iteration 10000 M( 63333333 )C, 0xa5d7a917d728239a, n = 4194304, MacLucasFFTW v8.1 Ballester M( 63333333 )C, 0xa5d7a917d728239a, n = 4194304, MacLucasFFTW v8.1 Ballester real 4m6.204s user 0m1.348s sys 0m0.496s 4096k fft sec/iter = 0.0246 Thank you, |
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2009-11-10, 21:23
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#55 |
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Jul 2003
So Cal
51478 Posts |
Version u is much better, but still about 5% slower than version k.
Version k: 0.0264 sec/iter Version o: 0.0278 sec/iter Version u: 0.0277 sec/iter Here's the updated profiler graph. transpose no longer dominates the runtime. |
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