LaurieWired/tailslayerPublic

Library for reducing tail latency in RAM reads

AI summary: A C++ library designed to reduce tail latency in RAM reads caused by DRAM refresh stalls.

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+3 today
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C++Apache-2.0Created Apr 5, 2026Last push 5mo ago+6 stars this week+25 this month

Quick answers

What is tailslayer?
A C++ library designed to reduce tail latency in RAM reads caused by DRAM refresh stalls.
What does tailslayer do?
Tailslayer is a highly specialized C++ library engineered to mitigate extreme tail latency in RAM reads, a problem typically caused by unavoidable DRAM refresh stalls. It achieves this by replicating data across multiple, independent DRAM channels that possess uncorrelated refresh schedules. The library creatively utilizes undocumented channel scrambling offsets—compatible across major CPU architectures like AMD, Intel, and AWS Graviton—to ensure data distribution. When a read request is initiated, Tailslayer issues concurrent, hedged reads across all replicas, allowing the application to proceed immediately with whichever memory channel responds first.
Who is tailslayer for?
Performance engineers, high-frequency traders, and systems developers requiring deterministic, ultra-low latency memory access in C++ applications.
How do I get started with tailslayer?
make
How popular is tailslayer on GitHub?
LaurieWired/tailslayer has 2,852 stars and 164 forks on GitHub, and gained 6 stars in the last 7 days.
What license does tailslayer use?
LaurieWired/tailslayer is released under the Apache-2.0 license.

Star history

since Jul 28, 2026
01K2KJul 2026Aug 2026Sep 2026Oct 2026
2.9K stars as of Oct 3, 2026. Measured daily since Jul 28, 2026; GitHub no longer exposes earlier star timestamps.

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13 commits in the last yearLessMore

Signals and awards

derived from tracked data
  • Permissive license

    Apache-2.0

What tailslayer does

Tailslayer is a highly specialized C++ library engineered to mitigate extreme tail latency in RAM reads, a problem typically caused by unavoidable DRAM refresh stalls. It achieves this by replicating data across multiple, independent DRAM channels that possess uncorrelated refresh schedules. The library creatively utilizes undocumented channel scrambling offsets—compatible across major CPU architectures like AMD, Intel, and AWS Graviton—to ensure data distribution. When a read request is initiated, Tailslayer issues concurrent, hedged reads across all replicas, allowing the application to proceed immediately with whichever memory channel responds first.

Performance engineers, high-frequency traders, and systems developers requiring deterministic, ultra-low latency memory access in C++ applications.

  • DRAM refresh mitigation: Actively counteracts extreme tail latency spikes caused by periodic, hardware-level DRAM refresh cycles.
  • Cross-channel data replication: Distributes data copies across independent memory channels possessing uncorrelated refresh schedules.
  • Hardware-level scrambling: Exploits undocumented channel scrambling offsets to optimize memory access on modern CPU architectures.
  • Concurrent hedged requests: Issues simultaneous read requests across multiple channels to bypass stalled memory banks effectively.
  • Multi-architecture compatibility: Validated to function correctly across AMD, Intel, and AWS Graviton processors.

Where teams use it

High-Frequency Trading

Financial engineers integrate the library into trading platforms to guarantee microsecond-level latency consistency by avoiding unpredictable DRAM stalls.

Real-Time Operating Systems

Embedded systems developers utilize the replication strategy to ensure deterministic read times for critical, time-sensitive applications.

In-Memory Database Optimization

Database architects reduce worst-case query latency and improve overall throughput in high-performance caching systems.

Performance Profiling

Systems programmers use the provided discovery tools to accurately measure and characterize DRAM refresh behavior on new hardware architectures.

Getting started: make

README

main branch

License GitHub stars GitHub forks GitHub contributors Follow @lauriewired

tailslayer3

Tailslayer

Tailslayer is a C++ library that reduces tail latency in RAM reads caused by DRAM refresh stalls.

It replicates data across multiple, independent DRAM channels with uncorrelated refresh schedules, using (undocumented!) channel scrambling offsets that works on AMD, Intel, and Graviton. Once the request comes in, Tailslayer issues hedged reads across all replicas, allowing the work to be performed on whichever result responds first.

cross_platform_nway

Usage

The library code is available in hedged_reader.cpp and the example using the library can be found in tailslayer_example.cpp. To use it, copy include/tailslayer into your project and #include <tailslayer/hedged_reader.hpp>. The library currently works with two channels (updates to come!), but full N-way usage is available in the benchmark.

You provide the value type and two functions as template parameters:

  1. Signal function: Add the loop that waits for the external signal. This determines when to read. Return the desired index to read, and the read immediately fires.
  2. Final work function: This receives the value immediately after it is read. Add the desired value processing code here.
#include <tailslayer/hedged_reader.hpp>

[[gnu::always_inline]] inline std::size_t my_signal() {
    // Wait for your event, then return the index to read
    return index_to_read;
}

template <typename T>
[[gnu::always_inline]] inline void my_work(T val) {
    // Use the value
}

int main() {
    using T = uint8_t;
    tailslayer::pin_to_core(tailslayer::CORE_MAIN);

    tailslayer::HedgedReader<T, my_signal, my_work<T>> reader{};
    reader.insert(0x43);
    reader.insert(0x44);
    reader.start_workers();
}

Arguments can be passed to either function via ArgList:

tailslayer::HedgedReader<T, my_signal, my_work<T>,
    tailslayer::ArgList<1, 2>,   // args to signal function
    tailslayer::ArgList<2>       // args to final work function
> reader{};

You can also optionally pass in a different channel offset, channel bit, and number of replicas to the constructor. Note: Each insert copies the element N times where N is the number of replicas. It does the address calculation work on the backend, allowing tailslayer to act as a hedged vector that uses logical indices. Additionally, each replica is pinned to a separate core, and will spin on that core according to the signal function until the read happens.

Build the example

make
./tailslayer_example

Benchmarks and spike timing

The discovery/ directory contains supporting code used to characterize DRAM refresh behavior:

  • discovery/benchmark/: Channel-hedged read benchmark
  • discovery/trefi_probe.c: Spike timing probe for measuring the refresh cycle
cd discovery/benchmark
make
sudo chrt -f 99 ./hedged_read_cpp --all --channel-bit 8
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Apr 8, 2026daily#18+159