Rename fractal-brain to Resonance_Engine: update all paths, docs, scripts, and add experiments/results/src
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Scruff AI
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/* ============================================================================
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* SIMPLE REALITY CHECK - 15 MINUTE TEST
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* Minimal test to verify basic physics works
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*
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* Tests:
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* 1. Does LBM run without crashing?
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* 2. What's the actual steps/sec?
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* 3. Does power scale?
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* 4. Does entropy vary?
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* ============================================================================ */
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#include <cuda_runtime.h>
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#include <nvml.h>
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#include <cstdio>
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#include <cstdlib>
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#include <cmath>
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#include <chrono>
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#define NX 1024
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#define NY 1024
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#define NN (NX * NY)
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#define Q 9
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#define BLOCK 256
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#define GBLK(n) (((n) + BLOCK - 1) / BLOCK)
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#define OMEGA 1.0f
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#define STEPS 500000 // Target: ~15 minutes at 5.5k steps/sec
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__constant__ int d_ex[Q] = { 0, 1, 0,-1, 0, 1,-1,-1, 1 };
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__constant__ int d_ey[Q] = { 0, 0, 1, 0,-1, 1, 1,-1,-1 };
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__constant__ float d_w[Q] = { 4.f/9, 1.f/9, 1.f/9, 1.f/9, 1.f/9,
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1.f/36,1.f/36,1.f/36,1.f/36 };
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__global__ void lbm_collide_stream_simple(const float* __restrict__ f_src,
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float* __restrict__ f_dst,
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float omega, int nx, int ny) {
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const int idx = blockIdx.x * blockDim.x + threadIdx.x;
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const int N = nx * ny;
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if (idx >= N) return;
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const int x = idx % nx, y = idx / nx;
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float fl[Q];
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for (int i = 0; i < Q; i++) {
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int sx = (x - d_ex[i] + nx) % nx;
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int sy = (y - d_ey[i] + ny) % ny;
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fl[i] = f_src[i * N + sy * nx + sx];
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}
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float rho = 0.f, ux = 0.f, uy = 0.f;
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for (int i = 0; i < Q; i++) {
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rho += fl[i];
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ux += (float)d_ex[i] * fl[i];
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uy += (float)d_ey[i] * fl[i];
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}
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float inv = 1.f / fmaxf(rho, 1e-10f);
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ux *= inv; uy *= inv;
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const float u2 = ux * ux + uy * uy;
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for (int i = 0; i < Q; i++) {
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float eu = (float)d_ex[i] * ux + (float)d_ey[i] * uy;
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float feq = d_w[i] * rho * (1.f + 3.f*eu + 4.5f*eu*eu - 1.5f*u2);
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f_dst[i * N + idx] = fl[i] - omega * (fl[i] - feq);
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}
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}
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float compute_variance(const float* ux, const float* uy) {
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float sum_ux = 0.f, sum_uy = 0.f;
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float sum_ux2 = 0.f, sum_uy2 = 0.f;
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for (int i = 0; i < NN; i++) {
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sum_ux += ux[i];
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sum_uy += uy[i];
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sum_ux2 += ux[i] * ux[i];
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sum_uy2 += uy[i] * uy[i];
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}
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float mean_ux = sum_ux / NN;
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float mean_uy = sum_uy / NN;
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float var_ux = (sum_ux2 / NN) - (mean_ux * mean_ux);
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float var_uy = (sum_uy2 / NN) - (mean_uy * mean_uy);
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return var_ux + var_uy;
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}
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int main() {
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printf("=======================================================================\n");
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printf(" SIMPLE REALITY CHECK - 15 MINUTE TEST\n");
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printf(" Beast: RTX 4090, 1024x1024 grid\n");
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printf(" Target: 500k steps (~15 min at 5.5k steps/sec)\n");
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printf("=======================================================================\n\n");
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// CUDA setup
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cudaDeviceProp prop;
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cudaGetDeviceProperties(&prop, 0);
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printf("[CUDA] %s SM %d.%d SMs: %d\n",
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prop.name, prop.major, prop.minor, prop.multiProcessorCount);
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// NVML power monitoring
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nvmlInit();
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nvmlDevice_t nvml_dev;
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nvmlDeviceGetHandleByIndex(0, &nvml_dev);
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unsigned int power_mW;
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nvmlDeviceGetPowerUsage(nvml_dev, &power_mW);
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printf("[NVML] Idle power: %.1f W\n", power_mW / 1000.0f);
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// Allocate memory
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float *f0, *f1, *ux, *uy;
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cudaMallocManaged(&f0, Q * NN * sizeof(float));
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cudaMallocManaged(&f1, Q * NN * sizeof(float));
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cudaMallocManaged(&ux, NN * sizeof(float));
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cudaMallocManaged(&uy, NN * sizeof(float));
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// Initialize
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printf("\n[INIT] Setting up equilibrium state...\n");
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for (int i = 0; i < Q * NN; i++) {
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f0[i] = 1.0f + 0.01f * (rand() / (float)RAND_MAX - 0.5f);
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}
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// Run test
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printf("\n[RUN] Starting %d step test...\n", STEPS);
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printf(" Batch | Steps | Variance | Power | Steps/sec\n");
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printf(" ------|---------|------------|-------|-----------\n");
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auto t0 = std::chrono::steady_clock::now();
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int cur = 0;
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int batch_size = 1000;
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int num_batches = STEPS / batch_size;
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FILE* csv = fopen("simple_reality_check.csv", "w");
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fprintf(csv, "steps,variance,power_w\n");
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for (int batch = 0; batch < num_batches; batch++) {
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// Run batch
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for (int s = 0; s < batch_size; s++) {
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lbm_collide_stream_simple<<<GBLK(NN), BLOCK>>>(
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(cur == 0) ? f0 : f1,
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(cur == 0) ? f1 : f0,
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OMEGA, NX, NY);
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cudaDeviceSynchronize();
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cur = 1 - cur;
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}
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// Measure every 10 batches
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if ((batch + 1) % 10 == 0) {
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uint64_t current_steps = (batch + 1) * batch_size;
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// Compute variance (simple entropy proxy)
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float variance = compute_variance(ux, uy);
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// Get power
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nvmlDeviceGetPowerUsage(nvml_dev, &power_mW);
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float power_W = power_mW / 1000.0f;
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// Compute steps/sec
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auto t_now = std::chrono::steady_clock::now();
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double elapsed = std::chrono::duration<double>(t_now - t0).count();
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float steps_per_sec = current_steps / elapsed;
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// Log
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fprintf(csv, "%llu,%.6e,%.1f\n", current_steps, variance, power_W);
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printf(" %5d | %7llu | %.3e | %5.0f | %8.0f\n",
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batch + 1, current_steps, variance, power_W, steps_per_sec);
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}
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// Check time limit
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auto t_now = std::chrono::steady_clock::now();
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double elapsed = std::chrono::duration<double>(t_now - t0).count();
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if (elapsed > 900.0) { // 15 minutes
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printf("\n[TIME] 15 minutes reached\n");
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break;
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}
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}
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auto t_end = std::chrono::steady_clock::now();
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double runtime = std::chrono::duration<double>(t_end - t0).count();
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uint64_t total_steps = num_batches * batch_size;
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float steps_per_sec = total_steps / runtime;
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printf("\n=======================================================================\n");
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printf(" RESULTS\n");
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printf("=======================================================================\n");
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printf("\nPERFORMANCE:\n");
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printf(" Total steps: %llu\n", total_steps);
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printf(" Runtime: %.1f seconds (%.1f minutes)\n", runtime, runtime / 60.0);
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printf(" Steps/sec: %.0f\n", steps_per_sec);
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printf(" Expected: ~5,500 steps/sec\n");
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nvmlDeviceGetPowerUsage(nvml_dev, &power_mW);
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printf("\nPOWER:\n");
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printf(" Final power: %.1f W\n", power_mW / 1000.0f);
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printf(" Idle power: ~37 W\n");
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printf(" Load power: ~290 W\n");
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printf("\n=======================================================================\n");
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printf(" V E R D I C T\n");
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printf("=======================================================================\n");
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if (steps_per_sec > 4000 && steps_per_sec < 7000) {
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printf("✅ PERFORMANCE REALITY: %.0f steps/sec (matches ~5.5k baseline)\n", steps_per_sec);
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} else {
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printf("❌ PERFORMANCE SUSPECT: %.0f steps/sec (expected ~5.5k)\n", steps_per_sec);
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}
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if (power_mW / 1000.0f > 100.0f) {
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printf("✅ POWER SCALING: %.1f W (above idle, real work)\n", power_mW / 1000.0f);
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} else {
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printf("❌ POWER SUSPECT: %.1f W (not scaling with load)\n", power_mW / 1000.0f);
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}
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printf("\nData saved: simple_reality_check.csv\n");
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// Cleanup
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fclose(csv);
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cudaFree(f0); cudaFree(f1);
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cudaFree(ux); cudaFree(uy);
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nvmlShutdown();
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return 0;
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}
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