# LaurieWired/tailslayer

Library for reducing tail latency in RAM reads

Repository: https://github.com/LaurieWired/tailslayer
Canonical: https://ross.abutalabs.com/products/tailslayer
Language: C++
License: Apache-2.0
License Family: permissive
Last push: 2026-04-11T23:41:40+00:00

## Health v2 (maintenance only)
Score: 48/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 76, release rhythm 35, longevity 10
- inputs: {"age_days": 150, "days_push": 144, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, young
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 2817, forks 162 (observed 2026-08-28T04:07:23.896497+00:00)

## What it is
Tailslayer is a C++ header-only library that reduces tail latency in RAM reads caused by DRAM refresh stalls. It replicates data across independent DRAM channels with uncorrelated refresh schedules and issues hedged reads, using whichever replica responds first.

## Use cases
- reduce tail latency of memory reads
- hide DRAM refresh stalls in low-latency systems
- hedge reads across DRAM channels
- build low-latency trading or HPC hot paths
- replicate hot data across memory channels

## When to choose
- you need to shave microseconds off p99 memory read latency
- you run on AMD, Intel, or Graviton hardware and can pin to cores
- your workload is dominated by DRAM refresh stalls on a small hot dataset

## When to avoid
- your dataset is too large to replicate across channels
- you need portability across arbitrary memory configurations
- you want a mature, widely production-tested solution

## Facets
- artifact type: library
- maturity: experimental
- function: concurrency, developer-tools
- domain: performance, hardware, developer-tools
- platform: cpp, cross-platform
- tags: tail-latency, dram-refresh, hedged-reads, low-latency, memory, performance, linux

## Member repositories
- LaurieWired/tailslayer (main) score 48

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:07:23.896497+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T08:13:01.875651+00:00, confidence not recorded.
  - readme: https://github.com/LaurieWired/tailslayer (fetched 2026-08-28T04:07:23.896497+00:00, sha 1ca23cd4c018)
- Data as of 2026-08-30T08:39:29.467469+00:00.