def test_mandelbrot_fpga():
mandelbrot = import_sample(Path("simple") / "mandelbrot.py")
h, w, max_iterations = 64, 64, 1000
out = dace.ndarray([h, w], dtype=dace.uint16)
out[:] = dace.uint32(0)
sdfg = mandelbrot.mandelbrot.to_sdfg()
sdfg.apply_transformations(FPGATransformSDFG)
sdfg(output=out, MAXITER=max_iterations, W=w, H=h)
return sdfg
def test_naive_matmul_fpga():
matmul = import_sample(Path("optimization") / "matmul.py")
sdfg = matmul.matmul.to_sdfg()
sdfg.apply_transformations(FPGATransformSDFG)
n, k, m = 64, 64, 64
A = np.random.rand(m, k).astype(np.float64)
B = np.random.rand(k, n).astype(np.float64)
C = np.zeros((m, n), dtype=np.float64)
sdfg(A=A, B=B, C=C, N=n, K=k, M=m)
expected = A @ B
diff = np.linalg.norm(C - expected) / (m * n)
assert diff <= 1e-6
return sdfg
def test_systolic_matmul_fpga():
matmul = import_sample(Path("fpga") / "matrix_multiplication_systolic.py")
return matmul.run_matmul_systolic(128, 32, 64, 4, False)
def test_spmv_fpga():
spmv = import_sample(Path("fpga") / "spmv_fpga_stream.py")
return spmv.run_spmv(64, 64, 640, False)
def test_jacobi_fpga():
jacobi = import_sample(Path("fpga") / "jacobi_fpga_systolic.py")
return jacobi.run_jacobi(64, 512, 16, 4)
def test_gemv_fpga():
gemv = import_sample(Path("fpga") / "gemv_fpga.py")
return gemv.run_gemv(1024, 1024, False)