# GPU Performance Details: Quadro 600
Contents: | System Configuration Results for datatype double MTimes (double) Backslash (double) FFT (double) Results for datatype single MTimes (single) Backslash (single) FFT (single)
## System Configuration
| Note that this is previously stored data and does not reflect your system configuration.
MATLAB Release: R2016a
Host
Name | Intel(R) Xeon(R) CPU E5-1620 0 @ 3.60GHz
Clock | 3601 MHz
Cache | 1024 KB
NumProcessors | 4
OSType | Windows
OSVersion | Microsoft Windows 7 Enterprise
| GPU
Name | Quadro 600
Clock | 1280 MHz
NumProcessors | 2
ComputeCapability | 2.1
TotalMemory | 1.00 GB
CUDAVersion | 7.5
DriverVersion | 8.17.13.5456 (354.56)
## Results for MTimes (double) These results show the performance of the GPU or host PC when calculating a matrix multiplication of two NxN real matrices. The number of operations is assumed to be `2*N^3 - N^2`. This calculation is usually compute-bound, i.e. the performance depends mainly on how fast the GPU or host PC can perform floating-point operations.
Raw data for Quadro 600 - MTimes (double)
Array size (elements) | Num Operations | Time (ms) | GigaFLOPS
--- | --- | --- | ---
1,024 | 64,512 | 0.06 | 1.03
4,096 | 520,192 | 0.09 | 5.57
16,384 | 4,177,920 | 0.34 | 12.35
65,536 | 33,488,896 | 1.90 | 17.58
262,144 | 268,173,312 | 13.91 | 19.28
1,048,576 | 2,146,435,072 | 109.08 | 19.68
4,194,304 | 17,175,674,880 | 866.61 | 19.82
(`N` gigaflops = `Nx109` operations per second)
## Results for Backslash (double) These results show the performance of the GPU or host PC when calculating the matrix left division of an `NxN` matrix with an `Nx1` vector. The number of operations is assumed to be `2/3*N^3 + 3/2*N^2`. This calculation is usually compute-bound, i.e. the performance depends mainly on how fast the GPU or host PC can perform floating-point operations.
Raw data for Quadro 600 - Backslash (double)
Array size (elements) | Num Operations | Time (ms) | GigaFLOPS
--- | --- | --- | ---
1,024 | 23,381 | 0.41 | 0.06
4,096 | 180,907 | 0.47 | 0.39
16,384 | 1,422,677 | 0.73 | 1.95
65,536 | 11,283,115 | 3.42 | 3.30
262,144 | 89,871,701 | 10.27 | 8.75
1,048,576 | 717,400,747 | 52.69 | 13.62
4,194,304 | 5,732,914,517 | 362.14 | 15.83
(`N` gigaflops = `Nx109` operations per second)
## Results for FFT (double) These results show the performance of the GPU or host PC when calculating the Fast-Fourier-Transform of a vector of complex numbers. The number of operations for a vector of length `N` is assumed to be `5*N*log2(N)`. This calculation is usually memory-bound, i.e. the performance depends mainly on how fast the GPU or host PC can read and write data.
Raw data for Quadro 600 - FFT (double)
Array size (elements) | Num Operations | Time (ms) | GigaFLOPS
--- | --- | --- | ---
1,024 | 51,200 | 0.09 | 0.57
4,096 | 245,760 | 0.14 | 1.73
16,384 | 1,146,880 | 0.27 | 4.19
65,536 | 5,242,880 | 0.83 | 6.33
262,144 | 23,592,960 | 3.31 | 7.13
1,048,576 | 104,857,600 | 13.94 | 7.52
4,194,304 | 461,373,440 | 66.36 | 6.95
(`N` gigaflops = `Nx109` operations per second)
## Results for MTimes (single) These results show the performance of the GPU or host PC when calculating a matrix multiplication of two NxN real matrices. The number of operations is assumed to be `2*N^3 - N^2`. This calculation is usually compute-bound, i.e. the performance depends mainly on how fast the GPU or host PC can perform floating-point operations.
Raw data for Quadro 600 - MTimes (single)
Array size (elements) | Num Operations | Time (ms) | GigaFLOPS
--- | --- | --- | ---
1,024 | 64,512 | 0.06 | 1.07
4,096 | 520,192 | 0.08 | 6.58
16,384 | 4,177,920 | 0.18 | 23.35
65,536 | 33,488,896 | 0.44 | 76.41
262,144 | 268,173,312 | 2.60 | 103.23
1,048,576 | 2,146,435,072 | 18.67 | 114.96
4,194,304 | 17,175,674,880 | 147.46 | 116.48
16,777,216 | 137,422,176,256 | 1171.99 | 117.26
(`N` gigaflops = `Nx109` operations per second)
## Results for Backslash (single) These results show the performance of the GPU or host PC when calculating the matrix left division of an `NxN` matrix with an `Nx1` vector. The number of operations is assumed to be `2/3*N^3 + 3/2*N^2`. This calculation is usually compute-bound, i.e. the performance depends mainly on how fast the GPU or host PC can perform floating-point operations.
Raw data for Quadro 600 - Backslash (single)
Array size (elements) | Num Operations | Time (ms) | GigaFLOPS
--- | --- | --- | ---
1,024 | 23,381 | 0.39 | 0.06
4,096 | 180,907 | 0.35 | 0.52
16,384 | 1,422,677 | 0.52 | 2.72
65,536 | 11,283,115 | 2.48 | 4.55
262,144 | 89,871,701 | 6.86 | 13.10
1,048,576 | 717,400,747 | 25.59 | 28.03
4,194,304 | 5,732,914,517 | 107.41 | 53.38
16,777,216 | 45,838,150,315 | 605.35 | 75.72
(`N` gigaflops = `Nx109` operations per second)
## Results for FFT (single) These results show the performance of the GPU or host PC when calculating the Fast-Fourier-Transform of a vector of complex numbers. The number of operations for a vector of length `N` is assumed to be `5*N*log2(N)`. This calculation is usually memory-bound, i.e. the performance depends mainly on how fast the GPU or host PC can read and write data.
Raw data for Quadro 600 - FFT (single)
Array size (elements) | Num Operations | Time (ms) | GigaFLOPS
--- | --- | --- | ---
1,024 | 51,200 | 0.09 | 0.60
4,096 | 245,760 | 0.09 | 2.80
16,384 | 1,146,880 | 0.15 | 7.55
65,536 | 5,242,880 | 0.31 | 16.75
262,144 | 23,592,960 | 0.97 | 24.28
1,048,576 | 104,857,600 | 3.84 | 27.29
4,194,304 | 461,373,440 | 16.50 | 27.96
(`N` gigaflops = `Nx109` operations per second)
Generated by gpuBench v1.7: 2017-02-19 15:03:15 | Back to summary