cleanup and improved reporting for csr

opencl_fdfd/csr.py

@@ -1,4 +1,5 @@
 import numpy
+from numpy.linalg import norm
 
 import pyopencl
 import pyopencl.array
@@ -52,17 +53,15 @@ def create_ops(context):
     v_out[i] = dot;
     '''
 
-    v_out_args = ctype + ' *v_out, int v_len_half'
+    v_out_args = ctype + ' *v_out'
-    m_args = 'int m_nnz, int *m_row_ptr, int *m_col_ind, ' + ctype + ' *m_data'
+    m_args = 'int *m_row_ptr, int *m_col_ind, ' + ctype + ' *m_data'
     v_in_args = ctype + ' *v_in'
 
     spmv_kernel = ElementwiseKernel(context, operation=spmv_source, preamble=preamble,
                                     arguments=', '.join((v_out_args, m_args, v_in_args)))
 
     def spmv(v_out, m, v_in, e):
-        return spmv_kernel(v_out, (v_out.size - 1)//2,
+        return spmv_kernel(v_out, m.row_ptr, m.col_ind, m.data, v_in, wait_for=e)
-                           m.data.size, m.row_ptr, m.col_ind, m.data,
-                           v_in, wait_for=e)
 
     # -------------------------------------
 
@@ -93,7 +92,7 @@ def create_ops(context):
                                 dtype_out=ri_dtype,
                                 neutral='(double3)(0.0, 0.0, 0.0)',
                                 map_expr=update_ri_source,
-                                reduce_expr='a+b',
+                                reduce_expr='a + b',
                                 arguments=ctype + ' *r')
 
     def ri_update(r, e):
@@ -149,7 +148,7 @@ def cg(a, b, max_iters=10000, err_thresh=1e-6, context=None, queue=None, verbose
     ops = create_ops(context)
 
     x = pyopencl.array.zeros(queue, dtype=numpy.complex128, shape=b.shape)
-    v = pyopencl.array.empty_like(x)
+    v = pyopencl.array.zeros_like(x)
     p = pyopencl.array.zeros_like(x)
     r = pyopencl.array.to_device(queue, b)
     alpha = 1.0 + 0j
@@ -158,20 +157,19 @@ def cg(a, b, max_iters=10000, err_thresh=1e-6, context=None, queue=None, verbose
 
     m = CSRMatrix(queue, a)
 
-    e = ops['spmv'](v, m, x, [])
+    _, err2 = ops['ri_update'](r, [])
-    e = ops['xr_update'](x, p, r, v, 0.0, [e])
-    _, err2 = ops['ri_update'](r, [e])
 
     b_norm = numpy.sqrt(err2)
     print('b_norm check: ', b_norm)
 
     start_time2 = time.perf_counter()
 
+    success = False
     for k in range(max_iters):
         if verbose:
             print('[{:06d}] rho {:.4} alpha {:4.4}'.format(k, rho, alpha), end=' ')
         rho_prev = rho
-        e = ops['xr_update'](x, p, r, v, alpha, [e])
+        e = ops['xr_update'](x, p, r, v, alpha, [])
         rho, err2 = ops['ri_update'](r, [e])
         errs += [numpy.sqrt(err2) / b_norm]
 
@@ -179,17 +177,35 @@ def cg(a, b, max_iters=10000, err_thresh=1e-6, context=None, queue=None, verbose
             print('err', errs[-1])
 
         if errs[-1] < err_thresh:
-            time_elapsed = time.perf_counter() - start_time
+            success = True
-            print('Success, {} iterations in {} sec: {} iterations/sec'.format(k,
+            break
-                   time_elapsed, k/time_elapsed))
-            print('overhead', start_time2-start_time)
-            return x.get(), errs, True
         e = ops['p_update'](p, r, rho/rho_prev, [])
-        e.wait()
         ops['spmv'](v, m, p, [e]).wait()
+
+#        v2 = a @ p.get()
+#        print('norm', norm(v2 - v.get()))
+
         alpha = rho / pyopencl.array.dot(p, v).get()
 
         if k % 1000 == 0:
             print(k)
 
-    return x.get(), errs, False
+    '''
+    Done solving
+    '''
+    time_elapsed = time.perf_counter() - start_time
+
+    x = x.get()
+
+    if success:
+        print('Success', end='')
+    else:
+        print('Failure', end=', ')
+    print(', {} iterations in {} sec: {} iterations/sec \
+                  '.format(k, time_elapsed, k / time_elapsed))
+    print('final error', errs[-1])
+    print('overhead {} sec'.format(start_time2 - start_time))
+
+    print('Post-everything residual:', norm(a @ x - b) / norm(b))
+    return x
+