Architectural Insights & Engineering Postmortems.

Scaling Synthetix Cloud: How We Squeezed 10x Throughput From 128 GPU Ray Worker Pools

An exhaustive postmortem on debugging tail latency in PyTorch tensor serialization, eliminating GIL contention in async Rust executors, and building zero-copy shared memory IPC across NVLink clusters.

• Rust
• Ray
• NVLink
• IPC

1#[inline(always)]2pub async fn dispatch_tensor_block<T>(3    pool: &Arc<ShmRingBuffer>,4    tensor: TensorRef<CUDAHost>,5) -> Result<DmaFuture, IpcFault> {6    // bypass GIL using direct unified memory handle7    let handle = pool.acquire_unpinned_slot().await?;8    handle.zero_copy_splice(tensor.raw_ptr(), tensor.bytes())?;9    metrics::counter!("ipc.dma_dispatch").increment(1);10    Ok(handle.into_future())11}