//! GPU kernel validation via remu (RDNA3 ISA emulator). //! //! Runs matmul kernels in software before sending to hardware. //! No GPU required — catches OOB accesses, wrong SGPRs, etc. //! //! run: cargo test --test kfd_remu -- --nocapture use remu::work_group::WorkGroup; /// Extract .text section from an AMDGPU ELF code object (.co). /// Returns (instructions, code_offset_in_file). fn extract_text(co: &[u8]) -> Vec { // Minimal ELF64 parser — just find .text section assert!(co.len() > 64, "too small for ELF"); assert!(&co[0..4] == b"\x7fELF", "not ELF"); assert!(co[4] == 2, "not ELF64"); let shoff = u64::from_le_bytes(co[40..48].try_into().unwrap()) as usize; let shentsize = u16::from_le_bytes(co[58..60].try_into().unwrap()) as usize; let shnum = u16::from_le_bytes(co[60..62].try_into().unwrap()) as usize; let shstrndx = u16::from_le_bytes(co[62..64].try_into().unwrap()) as usize; // Find string table for section names let strtab_off = shoff + shstrndx * shentsize; let str_offset = u64::from_le_bytes(co[strtab_off + 24..strtab_off + 32].try_into().unwrap()) as usize; for i in 0..shnum { let sh = shoff + i * shentsize; let name_idx = u32::from_le_bytes(co[sh..sh + 4].try_into().unwrap()) as usize; let name_start = str_offset + name_idx; let name_end = co[name_start..].iter().position(|&b| b == 0).unwrap() + name_start; let name = std::str::from_utf8(&co[name_start..name_end]).unwrap_or(""); if name == ".text" { let offset = u64::from_le_bytes(co[sh + 24..sh + 32].try_into().unwrap()) as usize; let size = u64::from_le_bytes(co[sh + 32..sh + 40].try_into().unwrap()) as usize; let text = &co[offset..offset + size]; assert!(size % 4 == 0, ".text not 4-byte aligned"); return text .chunks_exact(4) .map(|c| u32::from_le_bytes(c.try_into().unwrap())) .collect(); } } panic!(".text section not found"); } /// Pack matmul kernargs: W(u64) B(u64) X(u64) Y(u64) M(u32) K(u32) N(u32) fn pack_kernargs(w: *const f32, b: *const f32, x: *const f32, y: *mut f32, m: u32, k: u32, n: u32) -> Vec { let mut args = vec![0u64; 6]; // 48 bytes = 6 u64s args[0] = w as u64; args[1] = b as u64; args[2] = x as u64; args[3] = y as u64; // M and K packed into one u64 (little-endian: M=low, K=high) args[4] = (m as u64) | ((k as u64) << 32); // N in low 32 bits args[5] = n as u64; args } fn run_matmul(co: &[u8], w: &[f32], b: &[f32], x: &[f32], y: &mut [f32], m: u32, k: u32, n: u32) { run_matmul_tiled(co, w, b, x, y, m, k, n, 32, 8); } fn run_matmul_blocked(co: &[u8], w: &[f32], b: &[f32], x: &[f32], y: &mut [f32], m: u32, k: u32, n: u32) { run_matmul_tiled(co, w, b, x, y, m, k, n, 128, 32); } fn run_matmul_tiled(co: &[u8], w: &[f32], b: &[f32], x: &[f32], y: &mut [f32], m: u32, k: u32, n: u32, tm: u32, tn: u32) { let kernel = extract_text(co); let args = pack_kernargs(w.as_ptr(), b.as_ptr(), x.as_ptr(), y.as_mut_ptr(), m, k, n); let num_wg_m = (m + tm - 1) / tm; let num_wg_n = (n + tn - 1) / tn; let num_wg = num_wg_m * num_wg_n; for wg_id in 0..num_wg { let mut wg = WorkGroup::new(1, [wg_id, 0, 0], [256, 1, 1], &kernel, args.as_ptr()); wg.exec_waves().expect(&format!("kernel fault in workgroup {wg_id}")); } } /// Reference matmul: Y = X @ W^T + B fn reference_matmul(w: &[f32], b: &[f32], x: &[f32], m: usize, k: usize, n: usize) -> Vec { let mut y = vec![0.0f32; n * m]; for ni in 0..n { for mi in 0..m { let mut sum = b[mi]; for ki in 0..k { sum += x[ni * k + ki] * w[mi * k + ki]; } y[ni * m + mi] = sum; } } y } #[test] fn test_matmul_identity_32x32() { let co = include_bytes!("../src/host/device/kfd/kernels/matmul.co"); let m = 32u32; let k = 32u32; let n = 8u32; // W = identity, B = 0.5, X = sequential let mut w = vec![0.0f32; (m * k) as usize]; for i in 0..m.min(k) { w[(i * k + i) as usize] = 1.0; } let b = vec![0.5f32; m as usize]; let x: Vec = (0..n * k).map(|i| i as f32 * 0.1).collect(); let mut y = vec![0.0f32; (n * m) as usize]; run_matmul(co, &w, &b, &x, &mut y, m, k, n); let expected = reference_matmul(&w, &b, &x, m as usize, k as usize, n as usize); for i in 0..y.len() { assert!( (y[i] - expected[i]).abs() < 1e-3, "mismatch at {i}: got {}, expected {}", y[i], expected[i] ); } println!("PASS: 32x32 batch=8 identity matmul (remu)"); } #[test] fn test_matmul_random_64x64() { let co = include_bytes!("../src/host/device/kfd/kernels/matmul.co"); let m = 64u32; let k = 64u32; let n = 8u32; // Deterministic pseudo-random let mut rng = 12345u64; let mut randf = || -> f32 { rng = rng.wrapping_mul(6364136223846793005).wrapping_add(1); ((rng >> 33) as f32 / (1u64 << 31) as f32) - 1.0 }; let w: Vec = (0..m * k).map(|_| randf() * 0.1).collect(); let b = vec![0.0f32; m as usize]; let x: Vec = (0..n * k).map(|_| randf()).collect(); let mut y = vec![0.0f32; (n * m) as usize]; run_matmul(co, &w, &b, &x, &mut y, m, k, n); let expected = reference_matmul(&w, &b, &x, m as usize, k as usize, n as usize); let max_err = y .iter() .zip(expected.iter()) .map(|(a, b)| (a - b).abs()) .fold(0.0f32, f32::max); // FP32 accumulation over K=64 terms can have ~1e-4 relative error // with values in [-1,1] range, absolute error can reach ~0.01 per term let max_abs = expected.iter().map(|x| x.abs()).fold(0.0f32, f32::max); let rel_err = max_err / max_abs.max(1e-6); println!("64x64 batch=8 max_err={max_err:.6} max_abs={max_abs:.2} rel_err={rel_err:.6}"); assert!(rel_err < 1e-4, "relative error too large: {rel_err}"); println!("PASS: 64x64 batch=8 random matmul (remu)"); } // ============ Register-blocked kernel tests ============ #[test] fn test_blocked_identity_128x128() { let co = include_bytes!("../src/host/device/kfd/kernels/matmul_blocked.co"); let m = 128u32; let k = 8u32; // one tile iteration let n = 32u32; let mut w = vec![0.0f32; (m * k) as usize]; for i in 0..k { w[(i * k + i) as usize] = 1.0; } let b = vec![0.5f32; m as usize]; let x: Vec = (0..n * k).map(|i| (i as f32) * 0.01).collect(); let mut y = vec![0.0f32; (n * m) as usize]; run_matmul_blocked(co, &w, &b, &x, &mut y, m, k, n); let expected = reference_matmul(&w, &b, &x, m as usize, k as usize, n as usize); let max_err = y.iter().zip(expected.iter()) .map(|(a, b)| (a - b).abs()) .fold(0.0f32, f32::max); println!("blocked 128x8 batch=32: max_err={max_err:.6}"); assert!(max_err < 1e-3, "max error too large: {max_err}"); println!("PASS: blocked 128x8 batch=32 identity (remu)"); } #[test] fn test_blocked_random_256x256() { let co = include_bytes!("../src/host/device/kfd/kernels/matmul_blocked.co"); let m = 256u32; let k = 64u32; // multiple tile iterations (64/8=8) let n = 32u32; let mut rng = 42u64; let mut randf = || -> f32 { rng = rng.wrapping_mul(6364136223846793005).wrapping_add(1); ((rng >> 33) as f32 / (1u64 << 31) as f32) - 1.0 }; let w: Vec = (0..m * k).map(|_| randf() * 0.1).collect(); let b = vec![0.0f32; m as usize]; let x: Vec = (0..n * k).map(|_| randf()).collect(); let mut y = vec![0.0f32; (n * m) as usize]; run_matmul_blocked(co, &w, &b, &x, &mut y, m, k, n); let expected = reference_matmul(&w, &b, &x, m as usize, k as usize, n as usize); let max_err = y.iter().zip(expected.iter()) .map(|(a, b)| (a - b).abs()) .fold(0.0f32, f32::max); let max_abs = expected.iter().map(|x| x.abs()).fold(0.0f32, f32::max); let rel_err = max_err / max_abs.max(1e-6); println!("blocked 256x64 batch=32: max_err={max_err:.6} rel_err={rel_err:.6}"); assert!(rel_err < 1e-4, "relative error too large: {rel_err}"); println!("PASS: blocked 256x64 batch=32 random (remu)"); }