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Everything filed under Performance, newest first.
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turbopuffer is pushing the frontier of search. To do that, we have to fundamentally redesign our storage architecture so the vector index is no longer primary.
6 min · 1,334 words
OxCaml - Stack Allocations and Locality
The motivation behind OxCaml is to make OCaml a great language for performance engineering, with the eventual goal being to upstream these language extensions to vanilla OCaml (OxCaml](https://oxcaml.org/)). OxCaml maintains backwards compatibility with OCaml, which implies that every OCaml program is a valid OxCaml program. The language extensions range from additions to the type system that rule out data races, to control over allocations that reduces garbage collection pressure, to management
7 min · 1,697 words
What Makes LLM Tokenization Slow?Exploring the performance of byte-pair encoding by optimizing a GPT-2 tokenizer.
Andrew Healey dissects GPT-2’s reference BPE tokenizer, measures what makes tokenization slow, and shows concrete optimizations on the hot path of LLM products.
11 min · 2,547 words
PlanetScale Released Text Search and We Have a Lot to Say (Part I)
Two BM25 optimizations and benchmark configuration changes inspired by PlanetScale's TIN benchmarks make ParadeDB's text search faster without changing its document identifiers.
14 min · 3,188 words
Why we built the fastest robust TTS model
Gradium's latest streaming TTS hits ~50ms time-to-first-audio while improving naturalness and hard cases like phone numbers—freeing latency budget for LLM turns and barge-in in voice agents.
2 min · 431 words
zenkai: The App Launcher I Wrote Because I Wanted Something Fast and Beautiful
Dayvster builds zenkai, a Zig + Qt6 cross-platform app launcher with ~140ms startup (sometimes ~20ms), 65+ themes, Lua plugins, and a sandbox—written as a hobby performance deep dive.
2 min · 571 words
Cut your AI spend with AI Gateway's Auto Router
Cloudflare AI Gateway now features a model router that evaluates request complexity using an edge-deployed classifier to select the optimal model. By balancing expected output quality against token costs, organizations can dramatically cut AI spend while maintaining performance.
7 min · 1,627 words
How to speed up the Rust compiler in September 2026
How to speed up the Rust compiler in September 2026 My last post](https://nnethercote.github.io/2026/07/31/how-to-speed-up-the-rust-compiler-in-july-2026.html) on the Rust compiler’s performance was two months ago and a lot has happened since then. Overall progress The measurements for the period 2026-07-29 to 2026-09-28 can be seen here](https://perf.rust-lang.org/compare.html?start=1a833e16546c2eb012758ddd499964fd8afee29e&stat=wall-time&tab=compile&end=c1070d69382b8d2f2eb65119c738a77d9e324c9e&
5 min · 1,212 words
Garbage Collection: Generational? Incremental? Both!
The third Language Summit talk was brought by Mark Shannon, who is the author of the incremental garbage collector implementation shipped in Python 3.14 that was reverted back to the generational garbage collector from Python 3.13 after reports of “significant memory pressure” in production environments. The original goal of the new incremental garbage collector was to reduce maximum pause times by an order of magnitude for larger heaps.
5 min · 1,173 words
Edward Kmett's week-old Turbo Haskell Compiler (THC) JITs GHC Core onto Truffle/GraalVM, supports AOT Native Image, polyglot FFI, Loom green threads, and can compile pandoc, happy, alex, and GHC itself.
2 min · 506 words
Effect 4.0 rebuilds the TypeScript effect system from the ground up: zero-dependency core, ~5× smaller bundles, ~6.4× concurrent throughput, 86% less memory per fiber, and a long-term support policy through at least 2029.
2 min · 433 words
What Is a Container, Really? Five Years of GPU Infrastructure
Beam Cloud recounts five years of GPU infrastructure: from ECS and Knative cold starts to a custom container runtime, FUSE lazy-loading, and what “container” actually means in production AI compute.
9 min · 2,132 words
Deser: Rethinking Rust Serialization
Armin Ronacher revisits Deser, an experimental Rust serialization library that inverts Serde’s visitor recursion into heap-backed sinks/emitters—trading some performance for lossless buffering, composable adapters, XML namespaces, and no stack overflow on deep nests.
2 min · 492 words
5x faster Edge Functions: How we replaced v8 isolates with Firecracker MicroVMs
About a billion Edge Functions run on Netlify every day — Sunweb personalizing pages, LotoQuébec routing traffic on a cookie check, and hundreds of thousands of other sites doing everything from personalization to routing to auth. All of it runs on a full JavaScript runtime that scales with our customers’ traffic.
8 min · 1,844 words
Why refactoring made our biggest file biggerCode entropy, measured, and the ratchet that stops it
Image Horse's AppShell grew from 3,250 to 3,806 lines during a month of intentional extraction. Chris Lane Jones explains measured line-count ratchets, why warnings failed, and why entropy is whack-a-mole you don't win—but can make visible.
5 min · 1,168 words
Eddie Aftandilian ships SafeRE 1.0, a linear-time Java regex library built with agents: differential testing vs the JDK, ReDoS resistance by construction, and performance that now beats JDK and RE2/J on Rebar workloads.
5 min · 1,062 words
As If Yesterday, in Partly in the Right, I asked where the information comes from when an agent produces a result, and what checks it. Today I have a sharper version of that question, and a new piece of evidence to ask it about.
13 min · 2,972 words
GrapheneOS – When an app is slow
A GrapheneOS user digs into why OsmAnd maps feel slower on a Pixel 8 than on stock Android, and how that search led to CoMaps and broader performance trade-offs on hardened phones.
1 min · 245 words
Accelerated Out of Core Shuffling
Benjamin Zaitlen explains RapidsMPF’s reusable out-of-core shuffler for distributed analytics—how spilling turns shuffle OOM headaches into a budgetable resource, and what it takes to push shuffle bandwidth toward terabytes per second.
15 min · 3,466 words
DeepSeek Elastic Compute (DSec)
# Computer Science > Distributed, Parallel, and Cluster Computing [Submitted on 19 Sep 2026] # Title:DeepSeek Elastic Compute (DSec): A Sandbox Infrastructure for Effective Agentic Training at Scale View PDF HTML (experimental) Abstract:Large-scale agentic training and evaluation with large language models (LLMs) rely on isolated, stateful execution environments in which models inspect repositories, invoke tools, execute commands, and interact with task-specific services. These workloads create sandboxes in large bursts, span heterogeneous functionality and isolation…
16 min · 3,693 words