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Jaakko Vanhala
2026-04-12 11:49:08 +03:00
parent 5e82c798b1
commit 5d4a553520
2 changed files with 0 additions and 51 deletions
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3
network-poc/node/Cargo.toml
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@@ -26,9 +26,6 @@ web-sys = { version = "0.3.68", features = [
] } ] }
serde = { version = "1.0", features = ["derive"] } serde = { version = "1.0", features = ["derive"] }
serde_json = "1.0" serde_json = "1.0"
burn = { version = "0.14.0", features = ["wgpu", "ndarray"] }
burn-wgpu = "0.14.0"
burn-ndarray = "0.14.0"
wasm-bindgen-futures = "0.4" wasm-bindgen-futures = "0.4"
console_error_panic_hook = "0.1.7" console_error_panic_hook = "0.1.7"
reqwest = { version = "0.12", default-features = false, features = ["json"] } reqwest = { version = "0.12", default-features = false, features = ["json"] }

48
network-poc/node/src/lib.rs
View File

@@ -3,8 +3,6 @@ use web_sys::{WebSocket, MessageEvent};
use std::cell::RefCell; use std::cell::RefCell;
use std::rc::Rc; use std::rc::Rc;
use std::sync::atomic::{AtomicU32, AtomicBool, Ordering}; use std::sync::atomic::{AtomicU32, AtomicBool, Ordering};
use burn::tensor::Tensor;
use burn::backend::{Wgpu, NdArray};
pub mod storage; pub mod storage;
pub mod sampling; pub mod sampling;
@@ -79,41 +77,6 @@ pub async fn worker_fetch(url: &str) -> Result<web_sys::Response, String> {
.map_err(|_| "ei Response".to_string()) .map_err(|_| "ei Response".to_string())
} }
// Geneerinen tensorilaskenta — toimii millä tahansa Burn-backendillä
fn run_matmul<B: burn::tensor::backend::Backend>(size: usize) -> String {
let device = Default::default();
let dist = burn::tensor::Distribution::Default;
let t1: Tensor<B, 2> = Tensor::random([size, size], dist, &device);
let t2: Tensor<B, 2> = Tensor::random([size, size], dist, &device);
let sum = t1.matmul(t2).sum();
format!("{:?}", sum)
}
// Päättelyfunktio — valitsee backendin automaattisesti
async fn run_ai_tensor_inference(difficulty: usize) -> String {
let load_pct = GPU_LOAD_PERCENT.load(Ordering::SeqCst);
if load_pct == 0 {
sleep_ms(2000).await;
return format!("Paused (0%). Lepäillään zZz..");
}
let active_workload_size = (difficulty as f32 * (load_pct as f32 / 100.0)) as usize;
let sleep_delay = (100 - load_pct) * 10;
if sleep_delay > 0 {
sleep_ms(sleep_delay as i32).await;
}
let use_gpu = HAS_WEBGPU.load(Ordering::SeqCst);
let (backend_name, result) = if use_gpu {
("WebGPU", run_matmul::<Wgpu>(active_workload_size))
} else {
("CPU/NdArray", run_matmul::<NdArray>(active_workload_size))
};
format!("PoC {} Matmul ({}x{}) >> {}", backend_name, active_workload_size, active_workload_size, result)
}
/// JS-exportti: tokenisoi tekstin ja palauttaa JSON-merkkijonon /// JS-exportti: tokenisoi tekstin ja palauttaa JSON-merkkijonon
/// Tokenizer ladataan IndexedDB:stä (täytyy olla ladattu aiemmin) /// Tokenizer ladataan IndexedDB:stä (täytyy olla ladattu aiemmin)
@@ -351,17 +314,6 @@ pub async fn start_agent_node(hub_url: String, has_webgpu: bool, device_info_jso
} }
} }
} // current_task == 4 || 5 } // current_task == 4 || 5
} else if msg.contains("ai_task") {
console_log!("Hub task vastaanotettu, ajetaan GPU:lla...");
let ws_for_async = ws_clone.clone();
let diff = if msg.contains(r#""difficulty":1024"#) { 1024 } else { 512 };
// Suoritetaan inference asynkronisesti erillisessä taaskissa välttääksemme UI-jäätymisen kokonaan
wasm_bindgen_futures::spawn_local(async move {
let result = run_ai_tensor_inference(diff).await;
let reply = format!("{{\"type\":\"result\", \"status\":\"success\", \"data\":\"{}\"}}", result);
let _ = ws_for_async.borrow().send_with_str(&reply);
});
} else if msg.contains("stats") { } else if msg.contains("stats") {
// Sivuutetaan statsit täällä, UI hallitsee ne aivan itse HTML:n puolella // Sivuutetaan statsit täällä, UI hallitsee ne aivan itse HTML:n puolella
} }