lpgauth
Torque - SIMD-accelerated JSON encoding and decoding
Torque is a high-performance JSON library for Elixir built on sonic-rs via Rustler NIFs. It targets workloads where JSON throughput is a bottleneck — think bidstream processing, high-volume API ingestion, or any hot path that spends meaningful time in encode/decode.
Why Torque?
Raw throughput on a 1.2 KB OpenRTB payload (Apple M2 Pro, OTP 28, Elixir 1.19):
Decode
| Library | ips | mean | median | p95 | p99 | memory |
|---|---|---|---|---|---|---|
| torque | 255.8K | 3.91 µs | 3.58 µs | 4.54 µs | 9.21 µs | 1.56 KB |
| simdjsone | 185.9K | 5.38 µs | 5.00 µs | 6.38 µs | 12.67 µs | 1.59 KB |
| jiffy | 152.4K | 6.56 µs | 5.83 µs | 8.58 µs | 15.75 µs | 1.56 KB |
| otp json | 130.9K | 7.64 µs | 7.17 µs | 9.33 µs | 16.50 µs | 7.73 KB |
| jason | 109.1K | 9.17 µs | 8.54 µs | 11.04 µs | 18.13 µs | 9.54 KB |
Encode
| Library | ips | mean | median | p95 | p99 | memory |
|---|---|---|---|---|---|---|
| torque encode (proplist) | 869.6K | 1.15 µs | 1.04 µs | 1.29 µs | 1.42 µs | 88 B |
| torque iodata (proplist) | 854.7K | 1.17 µs | 1.08 µs | 1.33 µs | 1.46 µs | 64 B |
| torque iodata (map) | 775.2K | 1.29 µs | 1.17 µs | 1.46 µs | 1.63 µs | 64 B |
| torque encode (map) | 800.0K | 1.25 µs | 1.17 µs | 1.25 µs | 1.50 µs | 88 B |
| otp json (iodata) | 735.3K | 1.36 µs | 0.83 µs | 1.25 µs | 13.54 µs | 3928 B |
| jiffy | 537.6K | 1.86 µs | 1.63 µs | 2.00 µs | 2.29 µs | 120 B |
| otp json (binary) | 448.4K | 2.23 µs | 1.58 µs | 2.63 µs | 15.00 µs | 3992 B |
| jason | 284.9K | 3.51 µs | 2.42 µs | 14.63 µs | 16.63 µs | 3912 B |
Features
-
SIMD-accelerated decoding (AVX2/SSE2 on x86_64, NEON on ARM)
-
Ultra-low memory encoder — 64 B per encode vs ~4 KB for OTP
json/ Jason -
parse/1+get/2/get_many/2for selective field extraction (JSON Pointer / RFC 6901) -
Batch field extraction via a single NIF call
-
Automatic dirty CPU scheduler dispatch for large inputs
-
jiffy-compatible
{proplist}encoding for easy migration
Installation
elixir
def deps do
[{:torque, "~> 0.1.1"}]
end
Precompiled binaries are available for common targets. To build from source, install a stable Rust toolchain and set TORQUE_BUILD=true.
Most Liked
Asd
Given that your library uses SIMD instructions, precompiled binaries is a bad option, since precompilation works only for OS+CPU arch combination and it doesnt account for target CPU to have the proper flags which would indicate that it supports SIMD instructions
lpgauth
Hi, quick follow-up. I ended up adding specific binaries per CPU variants on x86_64.
https://github.com/lpgauth/torque?tab=readme-ov-file#cpu-optimized-variants
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