Speculative Branches

About a year ago, I published a post about an algorithm for randomness in floating point.

This post expands on an algorithm shown in the book I wrote on floating-point math.

When I recently looked at the state of the art in floating point random number generation, I was surprised to see a common procedure in many programming languages and libraries that is not really a floating-point algorithm: Generate a random integer with…

Twas about 4-6 weeks before Christmas, and all through the math department, not a creature was stirring, not even a plucky young undergrad.

I often like to have streams of trials playing in the background when I am working, and the recent trial of interest was the trial of Karen Read, who was accused of murder.

A guilty pleasure of mine is the pursuit of perfection.

Over the last year, as a person with a hardware background, I have heard a lot of complaints about Nvidia's dominance of the machine learning market and whether I can build chips to make the situation better.

This account comes from several publicly available sources as well as accounts from insiders who worked at Knight Capital Group at the time of the issue.

As you build a computer system, little things start to show up: maybe that database query is awkward for the feature you are building, or you find your server getting bogged down transferring gigabytes of data in hexadecimal ASCII, or your app translates…

I have recently been immersed in the theory and practice of random number generation while working on Arbitrand, a new high-quality true random number generation service hosted in AWS.

A modern CPU is an incredible machine.

Intel's Optane memory modules launched with a lot of fanfare in 2015, and were recently discontinued, in 2022, with similar fanfare.

A lot of ink is spent on the "monoliths vs. microservices" debate, but the real issue behind this debate is about whether distributed system architecture is worth the developer time and cost overheads.

In performance work, you will often find many distributions that are weirdly shaped: fat-tailed distributions, distributions with a hard lower bound at a non-zero number, and distributions that are just plain odd.

In 2018, I took the jump from being primarily an FPGA hardware engineer to being primarily a software engineer.

A post recently made the rounds on hacker news claiming that you should teach your kids poker, not chess.

When we think of how to represent fractional numbers in code, we reach for double and float, and almost never reach for anything else.

I have been working on another post recently, also related to division, but I wanted to address a comment I got from several people on the previous division article.

In honor of April Fools' Day, I decided to write about a blockchain topic.

Python and Assembly have one thing in common: as a professional software engineer, they are both languages that you probably should know how to read, but be terrified to write.

Occasionally, I like to peruse uops.info.

A lot of the time, when engineers think of performance work, we think about looking at benchmarks and making the numbers smaller.

When you design software to achieve a particular level of performance, it can be a good idea to be familiar with the general speed regimes you are working with: fundamental limitations like storage devices and networks can drive software architecture.

This is the second part in a 2-part series on the "Fibonacci" interview problem.

Few interview problems are as notorious as the "Fibonacci" interview question.

Hello everyone, and welcome to my blog.