GPU Applications (CUDA) |
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# | Benchmark Name | Domain | Description | Input Dataset | Error Metric | Language | Developed by | ||

1 | Binarization | Image processing | Binarization of a color-pixel image | Three 512x512 pixel images | Image Diff (RMSE) | C++/CUDA | NVIDIA SDK 6.5 | ||

2 | Black-Scholes | Financial Analysis | Mathematical model of a financial market | 48,000 options | Average Relative Error | C++/CUDA | NVIDIA SDK 6.5 | ||

3 | Convolution Separable | Image Processing | A separable convolution filter of a 2D signal with a gaussian kernel | 512x512-Pixel Image | Image Diff (RMSE) | C++/CUDA | NVIDIA SDK 6.5 | ||

4 | Inversek2j | Robotics | Inverse kinematics for 2-joint arm | 300,000 (x,y) coordinates | Average Relative Error | C++/CUDA | ACT-LAB | ||

5 | Jmeint | 3D gaming | Triangle intersection detection | 100,000 random pairs of 3D triangle coordinates | Miss Rate | C++/CUDA | Thomas Möller | ||

6 | Laplacian | Image processing | Image sharpening filter | Three 512x512 pixel images | Image Diff (RMSE) | C++/CUDA | NVIDIA SDK 6.5 | ||

7 | Mean Filter | Image Processing | Convolution Filter for Noise Reduction | 512x512-Pixel Image | Image Diff (RSME) | C++/CUDA | NVIDIA SDK 6.5 | ||

8 | Newton-Raphson | Numerical Analysis | Equation solver | 8,192 cubic equations | Image Diff (RMSE) | C++/CUDA | NVIDIA SDK 6.5 | ||

9 | Sobel | Image Processing | Sobel edge detector | 512x512 pixel color image | Image Diff (RMSE) | C++/CUDA | NVIDIA SDK 6.5 | ||

10 | Srad | Medical Imaging | Speckle Reducing Anisotropic Diffusion | 512x512 pixel color image | Image Diff (RMSE) | C++/CUDA | Rodinia |

CPU Applications |
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# | Benchmark Name | Domain | Description | Input Dataset | Error Metric | Language | Developed by | ||

1 | Black-Scholes | Financial Analysis | Mathematical model of a financial market | 48,000 options | Average Relative Error | C++ | PARSEC | ||

2 | FFT | Signal Processing | Radix-2 Colley-Tykey Fast Fourier | 32,767 random floating point numbers | Average Relative Error | C++ | ACT-LAB | ||

3 | Inversek2j | Robotics | Inverse kinematics for 2-joint arm | 300,000 (x,y) random coordinates | Average Relative Error | C++ | ACT-LAB | ||

4 | Jmeint | 3D gaming | Triangle intersection detection | 100,000 random pairs of 3D triangle coordinates | Miss Rate | C++ | Thomas Möller | ||

5 | JPEG encoder | Compression | JPEG encoding | 512x512 pixel color image | Image Diff (RMSE) | C++ | ACT-LAB | ||

6 | K-means | Machine Learning | K-means clustering | 262,144 paris of random (r,g,b) values | Image Diff (RMSE) | C++ | ACT-LAB | ||

7 | Sobel | Image Processing | Sobel edge detector | 512x512 pixel color image | Image Diff (RMSE) | C++ | ACT-LAB |

Verilog Applications |
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# | Benchmark Name | Domain | Description | Input Dataset | Error Metric | Language | Developed by | ||

1 | Brent-Kung | Arithmetic Computation | 32-bit Adder | 1,000,000 32-bit integers | Average Relative Error | Verilog | ACT-LAB | ||

2 | FIR | Signal Processing | 8-bit FIR Fitler | 1,000,000 8-bit integers | Average Relative Error | Verilog | ACT-LAB | ||

3 | Forwardk2j | Robotics | Forward kinematics for 2-joint arm | 1,000,000 32-bit fixed-point values | Average Relative Error | Verilog | ACT-LAB | ||

4 | Inversek2j | Robotics | Inverse kinematics for 2-join arm | 1,000,000 32-bit fixed-point values | Average Relative Error | Verilog | ACT-LAB | ||

5 | K-means | Machine Learning | K-means clustering | 1024x1024 pixel color image | Image Diff (RMSE) | Verilog | ACT-LAB | ||

6 | Kogge-Stone | Arithmetic Computation | 32-bit Adder | 1,000,000 32-bit integers | Average Relative Error | Verilog | ACT-LAB | ||

7 | Neural Network | Machine Learning | Feedforward neural network | 1024x1024 pixel color image | Image Diff (RMSE) | Verilog | ACT-LAB | ||

7 | Sobel | Image Processing | Sobel edge detector | 1024x1024 pixel color image | Image Diff (RMSE) | Verilog | ACT-LAB |