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 pavpanchekha.com
Floating Point Error in Polynomials
| | nhigham.com
Half Precision Arithmetic: fp16 Versus bfloat16 - Nick Higham
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| | The 2008 revision of the IEEE Standard for Floating-Point Arithmetic introduced a half precision 16-bit floating point format, known as fp16, as a storage format. Various manufacturers have adopted fp16 for computation, using the obvious extension of the rules for the fp32 (single precision) and fp64 (double precision) formats. For example, fp16 is supported by...
| | marc-b-reynolds.github.io
A fast path floating point underflow test elision from absorption
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| | A sketch of a fast path filter to avoid explicit underflow checking following an addition or subtraction.
| | www.jeremykun.com
Polynomial Multiplication Using the FFT | Math Programming
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| | Problem: Compute the product of two polynomials efficiently. Solution: import numpy from numpy.fft import fft, ifft def poly_mul(p1, p2): """Multiply two polynomials. p1 and p2 are arrays of coefficients in degree-increasing order. """ deg1 = p1.shape[0] - 1 deg2 = p1.shape[0] - 1 # Would be 2*(deg1 + deg2) + 1, but the next-power-of-2 handles the +1 total_num_pts = 2 * (deg1 + deg2) next_power_of_2 = 1 << (total_num_pts - 1).
| | yehudakatz.com
Exploring Ember Polaris: CSS Modules Without Addons
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| The Polaris edition of Ember sheds Emberisms in favor of integrating directly with the JavaScript ecosystem. This post shows how you can directly use CSS modules in modern Ember applications.