WritingThe cache was working perfectly. That was the problem.
A 99.2% hit rate hid nine cache stampedes. What singleflight fixed, what it did not, and the two bugs that only exist under concurrency.
Writing
Optimisation work, written up in long form — including the wrong turns.
The Bloom Filter Optimization Saga: The "Benign" Read That Wasn't
An atomic-first Go Bloom filter still tripped the race detector. A war story about the read that looked benign, and what the Go memory model has to say about it.
Finding Errors in Log Streams
Rank and select turn two expensive log queries into constant-time lookups. What that costs, what it buys, and why the same code can honestly report both 2ns and 13ns.
The Bloom Filter Optimization Saga: A Deep Dive into Go Assembly and AVX2
A line-by-line reading of avx2.s: runtime AVX2 detection, and hand-written Go assembly for population count, bitwise OR and AND, and clearing 32 bytes at a time.
The Bloom Filter Optimization Saga: Anatomy of a Go Concurrency Bug - Part 2
Making the Bloom filter thread-safe cost 8–12x in throughput. The culprit was a heap allocation on every Add and Contains; the fix was a stack array for small hash counts.
The Bloom Filter Optimization Saga: Anatomy of a Go Concurrency Bug - Part 1
Concurrent reads were panicking in a Go Bloom filter because Contains() quietly mutated shared scratchpad state. How the race was found, fixed, and what the fix cost.
The Bloom Filter Optimization Saga: From 3 Seconds to 66 Microseconds
A benchmark that measured fmt.Sprintf instead of the filter, several pprof sessions, one optimisation that made things worse, and the data-structure change that finally paid.
The most profound rules of software development.
Gall's Law, Lehman, Brooks, Wirth and the rest — each with the project that ignored it, the project that respected it, and a story from my own trenches.
CFD - Part 1
What computational fluid dynamics actually is — the history from Euler to WENO schemes, why analytical solutions and wind tunnels both hit walls, and where the hard parts lie.
The Equations of Everything That Flows
The Navier–Stokes equations from four playground ideas — mass, momentum, viscosity and pressure — through Euler, Navier and Stokes to the vector calculus that writes them down.
SIMD-Optimized Bloom Filter in Go: An In-Depth Exploration
A comprehensive exploration of a cache-line optimized Bloom filter implementation in Go with SIMD acceleration and assembly integration.
Solving the Pandigital Puzzle with AVX2 SIMD Acceleration.
Bringing AVX2 to Project Euler 38 — what 256-bit registers buy when the same pandigital check runs over thousands of candidates, and how the C++ compares to scalar code.
Solving Project Euler 38 with MATLAB: The Vectorized Pandigital Blitz
Vectorising Project Euler 38 in MATLAB: build the concatenated products as a matrix, test every candidate in one pass, and let the language do what it is actually good at.
Solving Pandigital Multiples with C# and Length‑Based Pruning
A C# solution that prunes by digit length instead of brute-forcing: the constraint that the products must total nine digits bounds k to a handful of ranges.
Optimizing Pandigital Multiples in Python
Turning the brute-force Python solution lean: integer concatenation instead of strings, a 10-bit mask for the pandigital test, and early exits that prune the search.
Programmatically Finding Pandigital Multiples
A step-by-step Python solution to Project Euler 38: why the search stops at 9999, how to build each concatenated product, and a straightforward pandigital check.
Project Euler 38: Solving with Pen and Paper Like It’s 1899 🖊️
Project Euler 38 without a computer: digit-count arithmetic narrows the search to four-digit numbers starting with 9, and the rest is pen, paper and a little logic.
The Fascinating World of Pandigital Multiples
What makes 192384576 special, and why concatenating the multiples of 9327 gives the largest 1–9 pandigital number you can build this way. No code, just the puzzle.
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