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blog.reverberate.org | ||
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james.darpinian.com
You may know that all numbers in JavaScript are 64 bit double-precision floating point values. This is sometimes convenient and it works pretty well as a default for novice programmers, who are often confused by integer math, and rightfully so when 1 / 2 = 0. Unfortunately, it makes things slow. Doubles take a lot of memory and floating point math is slower than integer math on CPUs. It's also inconvenient if you want to port existing code to JavaScript, because existing code usually expects to use integ... |
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projectf.io
Sometimes you need more precision than integers can provide, but floating-point computation is not trivial (try reading IEEE 754). You could use a library or IP block, but simple fixed point maths can often get the job done with little effort. Furthermore, most FPGAs have dedicated DSP blocks that make multiplication and addition of integers fast; we can take advantage of that with a fixed-point approach. |
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marc-b-reynolds.github.io
Computing Weyl (additive recurrence) sequences in float-point has some gotchas. |
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jeremykun.com
In this article I'll derive a trick used in FHE called sample extraction. In brief, it allows one to partially convert a ciphertext in the Ring Learning With Errors (RLWE) scheme to the Learning With Errors (LWE) scheme. Here are some other articles I've written about other FHE building blocks, though they are not prerequisites... |
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