Various algorithms
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Updated
Aug 19, 2018 - C++
Various algorithms
A demonstration of the use of SVD in image compression
Lightweight C# implementations of common "compensated sum" accumulators.
Several common methods of matrix multiplication are implemented on CPU and Nvidia GPU using C++11 and CUDA.
Kahan Floating-Point (C++ implementation)
Calculate the arithmetic mean of a single-precision floating-point strided array using a second-order iterative Kahan–Babuška algorithm.
Calculate the arithmetic mean of a single-precision floating-point strided array using an improved Kahan–Babuška algorithm.
Calculate the sum of strided array elements using an improved Kahan–Babuška algorithm.
Calculate the sum of strided array elements, ignoring NaN values and using an improved Kahan–Babuška algorithm.
Calculate the cumulative sum of strided array elements using a second-order iterative Kahan–Babuška algorithm.
Calculate the cumulative sum of strided array elements using an improved Kahan–Babuška algorithm.
Add a constant to each strided array element and compute the sum using a second-order iterative Kahan–Babuška algorithm.
Add a constant to each strided array element and compute the sum using an improved Kahan–Babuška algorithm.
Calculate the arithmetic mean of a double-precision floating-point strided array using a second-order iterative Kahan–Babuška algorithm.
Calculate the arithmetic mean of a double-precision floating-point strided array using an improved Kahan–Babuška algorithm.
Add a constant to each double-precision floating-point strided array element and compute the sum using an improved Kahan–Babuška algorithm.
Add a constant to each double-precision floating-point strided array element and compute the sum using a second-order iterative Kahan–Babuška algorithm.
Calculate the cumulative sum of double-precision floating-point strided array elements using an improved Kahan–Babuška algorithm.
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