optimize hessian & gpu timer

examples/00-h2o.py

@@ -24,7 +24,7 @@
 H       0.7570000000     0.0000000000    -0.4696000000
 '''
 
-xc='LDA'
+xc='B3LYP'
 bas='def2-tzvpp'
 auxbasis='def2-tzvpp-jkfit'
 scf_tol = 1e-10
@@ -34,7 +34,7 @@
 
 mol = pyscf.M(atom=atom, basis=bas, max_memory=32000)
 
-mol.verbose = 4
+mol.verbose = 6
 mf_GPU = rks.RKS(mol, xc=xc).density_fit(auxbasis=auxbasis)
 mf_GPU.grids.level = grids_level
 mf_GPU.conv_tol = scf_tol

examples/dft_driver.py

@@ -35,7 +35,7 @@
     basis=bas,
     max_memory=32000)
 # set verbose >= 6 for debugging timer
-mol.verbose = 6
+mol.verbose = 1
 
 mf_df = rks.RKS(mol, xc=args.xc).density_fit(auxbasis=args.auxbasis)
 if args.solvent:

gpu4pyscf/df/df.py

@@ -67,8 +67,8 @@ def build(self, direct_scf_tol=1e-14, omega=None):
         idx = np.arange(nao)
         self.diag_idx = cupy.asarray(idx*(idx+1)//2+idx)
 
-        t0 = (logger.process_clock(), logger.perf_counter())
         log = logger.new_logger(mol, mol.verbose)
+        t0 = log.init_timer()
         if auxmol is None:
             self.auxmol = auxmol = addons.make_auxmol(mol, self.auxbasis)
 
@@ -217,7 +217,7 @@ def cholesky_eri_gpu(intopt, mol, auxmol, cd_low, omega=None, sr_only=False):
     nq = len(intopt.log_qs)
     for cp_ij_id, _ in enumerate(intopt.log_qs):
         if len(intopt.ao_pairs_row[cp_ij_id]) == 0: continue
-        t1 = (logger.process_clock(), logger.perf_counter())
+        t1 = log.init_timer()
         cpi = intopt.cp_idx[cp_ij_id]
         cpj = intopt.cp_jdx[cp_ij_id]
         li = intopt.angular[cpi]

gpu4pyscf/df/df_jk.py

@@ -20,9 +20,9 @@
 import cupy
 import numpy
 from pyscf import lib, scf, __config__
-from pyscf.lib import logger
 from pyscf.scf import dhf
 from pyscf.df import df_jk, addons
+from gpu4pyscf.lib import logger
 from gpu4pyscf.lib.cupy_helper import contract, take_last2d, transpose_sum, load_library, get_avail_mem
 from gpu4pyscf.dft import rks, numint
 from gpu4pyscf.scf import hf
@@ -250,7 +250,7 @@ def get_jk(dfobj, dms_tag, hermi=1, with_j=True, with_k=True, direct_scf_tol=1e-
     nao = dms_tag.shape[-1]
     dms = dms_tag.reshape([-1,nao,nao])
     nset = dms.shape[0]
-    t0 = (logger.process_clock(), logger.perf_counter())
+    t0 = log.init_timer()
     if dfobj._cderi is None:
         log.debug('CDERI not found, build...')
         dfobj.build(direct_scf_tol=direct_scf_tol, omega=omega)

gpu4pyscf/df/grad/rhf.py

@@ -18,12 +18,12 @@
 import cupy
 from cupyx.scipy.linalg import solve_triangular
 from pyscf.df.grad import rhf
-from pyscf.lib import logger
 from pyscf import lib, scf, gto
 from gpu4pyscf.df import int3c2e
 from gpu4pyscf.lib.cupy_helper import print_mem_info, tag_array, unpack_tril, contract, load_library
 from gpu4pyscf.grad.rhf import grad_elec
 from gpu4pyscf import __config__
+from gpu4pyscf.lib import logger
 
 libcupy_helper = load_library('libcupy_helper')
 
@@ -154,7 +154,7 @@ def get_jk(mf_grad, mol=None, dm0=None, hermi=0, with_j=True, with_k=True, omega
         vkaux = cupy.zeros((3,naux_cart))
     cupy.get_default_memory_pool().free_all_blocks()
     for cp_kl_id in range(len(intopt.aux_log_qs)):
-        t1 = (logger.process_clock(), logger.perf_counter())
+        t1 = log.init_timer()
         k0, k1 = intopt.cart_aux_loc[cp_kl_id], intopt.cart_aux_loc[cp_kl_id+1]
         assert k1-k0 <= block_size
         if with_j:

gpu4pyscf/df/grad/rks.py

@@ -29,7 +29,7 @@ def get_veff(ks_grad, mol=None, dm=None):
     '''
     if mol is None: mol = ks_grad.mol
     if dm is None: dm = ks_grad.base.make_rdm1()
-    t0 = (logger.process_clock(), logger.perf_counter())
+    t0 = logger.init_timer(ks_grad)
 
     mf = ks_grad.base
     ni = mf._numint

gpu4pyscf/df/hessian/rhf.py

@@ -55,7 +55,7 @@ def _partial_hess_ejk(hessobj, mo_energy=None, mo_coeff=None, mo_occ=None,
     '''Partial derivative
     '''
     log = logger.new_logger(hessobj, verbose)
-    time0 = t1 = (logger.process_clock(), logger.perf_counter())
+    time0 = t1 = log.init_timer()
 
     mol = hessobj.mol
     mf = hessobj.base
@@ -393,12 +393,14 @@ def make_h1(hessobj, mo_coeff, mo_occ, chkfile=None, atmlst=None, verbose=None):
 def _gen_jk(hessobj, mo_coeff, mo_occ, chkfile=None, atmlst=None,
             verbose=None, with_k=True, omega=None):
     log = logger.new_logger(hessobj, verbose)
-    t0 = (logger.process_clock(), logger.perf_counter())
+    t0 = log.init_timer()
     mol = hessobj.mol
     if atmlst is None:
         atmlst = range(mol.natm)
     # FIXME
     with_k = True
+    mo_coeff = cupy.asarray(mo_coeff)
+    mo_occ = cupy.asarray(mo_occ)
 
     mf = hessobj.base
     #auxmol = hessobj.base.with_df.auxmol
@@ -441,16 +443,16 @@ def _gen_jk(hessobj, mo_coeff, mo_occ, chkfile=None, atmlst=None,
         rhok0_Pl_ = np.empty_like(wk_Pl_)
         for p0, p1 in lib.prange(0,nao,64):
             wk_tmp = cupy.asarray(wk_Pl_[:,p0:p1])
-            rhok0_Pl_[:,p0:p1] = cupy.einsum('pq,qio->pio', int2c_inv, wk_tmp).get()
+            rhok0_Pl_[:,p0:p1] = contract('pq,qio->pio', int2c_inv, wk_tmp).get()
     wj = wk_Pl_ = wk_P__ = int2c_inv = int2c = None
 
     # int3c_ip1 contributions
     vj1_buf, vk1_buf, vj1_ao, vk1_ao = int3c2e.get_int3c2e_ip1_vjk(intopt, rhoj0, rhok0_Pl_, dm0_tag, aoslices, omega=omega)
     vj1_buf = vj1_buf[cupy.ix_(numpy.arange(3), rev_ao_idx, rev_ao_idx)]
     vk1_buf = vk1_buf[cupy.ix_(numpy.arange(3), rev_ao_idx, rev_ao_idx)]
 
-    vj1_int3c_ip1 = -cupy.einsum('nxiq,ip->nxpq', vj1_ao, mo_coeff)
-    vk1_int3c_ip1 = -cupy.einsum('nxiq,ip->nxpq', vk1_ao, mo_coeff)
+    vj1_int3c_ip1 = -contract('nxiq,ip->nxpq', vj1_ao, mo_coeff)
+    vk1_int3c_ip1 = -contract('nxiq,ip->nxpq', vk1_ao, mo_coeff)
     vj1_ao = vk1_ao = None
     t0 = log.timer_debug1('Fock matrix due to int3c2e_ip1', *t0)
 
@@ -475,15 +477,15 @@ def _gen_jk(hessobj, mo_coeff, mo_occ, chkfile=None, atmlst=None,
 
         for p0, p1 in lib.prange(0,nao,64):
             rhok_tmp = cupy.asarray(rhok0_Pl_[:,p0:p1])
-            vj1_tmp = cupy.einsum('pio,xp->xpio', rhok_tmp, wj0_10)
+            vj1_tmp = contract('pio,xp->xpio', rhok_tmp, wj0_10)
 
-            wk0_10_Pl_ = cupy.einsum('xqp,pio->xqio', int2c_ip1, rhok_tmp)
-            vj1_tmp += cupy.einsum('xpio,p->xpio', wk0_10_Pl_, rhoj0)
-            vj1_int3c_ip2[:,:,p0:p1] += cupy.einsum('xpio,pa->axio', vj1_tmp, aux2atom)
+            wk0_10_Pl_ = contract('xqp,pio->xqio', int2c_ip1, rhok_tmp)
+            vj1_tmp += contract('xpio,p->xpio', wk0_10_Pl_, rhoj0)
+            vj1_int3c_ip2[:,:,p0:p1] += contract('xpio,pa->axio', vj1_tmp, aux2atom)
             if with_k:
-                vk1_tmp = 2.0 * cupy.einsum('xpio,pro->xpir', wk0_10_Pl_, rhok0_P__)
-                vk1_tmp += 2.0 * cupy.einsum('xpro,pir->xpio', wk0_10_P__, rhok_tmp)
-                vk1_int3c_ip2[:,:,p0:p1] += cupy.einsum('xpio,pa->axio', vk1_tmp, aux2atom)
+                vk1_tmp = 2.0 * contract('xpio,pro->xpir', wk0_10_Pl_, rhok0_P__)
+                vk1_tmp += 2.0 * contract('xpro,pir->xpio', wk0_10_P__, rhok_tmp)
+                vk1_int3c_ip2[:,:,p0:p1] += contract('xpio,pa->axio', vk1_tmp, aux2atom)
         wj0_10 = wk0_10_P__ = rhok0_P__ = int2c_ip1 = None
         vj1_tmp = vk1_tmp = wk0_10_Pl_ = rhoj0 = rhok0_Pl_ = None
         aux2atom = None
@@ -498,8 +500,8 @@ def _gen_jk(hessobj, mo_coeff, mo_occ, chkfile=None, atmlst=None,
 
     # ========================== sorted AO end ================================
     def _ao2mo(mat):
-        tmp = cupy.einsum('xij,jo->xio', mat, mocc)
-        return cupy.einsum('xik,ip->xpk', tmp, mo_coeff)
+        tmp = contract('xij,jo->xio', mat, mocc)
+        return contract('xik,ip->xpk', tmp, mo_coeff)
 
     vj1_int3c = vj1_int3c_ip1 + vj1_int3c_ip2
     vj1_int3c_ip1 = vj1_int3c_ip2 = None
@@ -522,7 +524,7 @@ def _ao2mo(mat):
             vk1_ao[:,:,p0:p1] -= vk1_buf[:,p0:p1,:].transpose(0,2,1)
 
         h1 = hcore_deriv(ia)
-        h1 = _ao2mo(h1)
+        h1 = _ao2mo(cupy.asarray(h1))
         vj1 = vj1_int3c[ia] + _ao2mo(vj1_ao)
         if with_k:
             vk1 = vk1_int3c[ia] + _ao2mo(vk1_ao)

gpu4pyscf/df/hessian/rks.py

@@ -37,7 +37,7 @@
 def partial_hess_elec(hessobj, mo_energy=None, mo_coeff=None, mo_occ=None,
                       atmlst=None, max_memory=4000, verbose=None):
     log = logger.new_logger(hessobj, verbose)
-    time0 = t1 = (logger.process_clock(), logger.perf_counter())
+    time0 = t1 = log.init_timer()
 
     mol = hessobj.mol
     mf = hessobj.base

gpu4pyscf/df/int3c2e.py

@@ -184,7 +184,7 @@ def build(self, cutoff=1e-14, group_size=None,
         a tot_mol is created with concatenating [mol, fake_mol, aux_mol]
         we will pair (ao,ao) and (aux,1) separately.
         '''
-        cput0 = (logger.process_clock(), logger.perf_counter())
+        cput0 = logger.init_timer(self.mol)
         sorted_mol, sorted_idx, uniq_l_ctr, l_ctr_counts = sort_mol(self.mol)
         if group_size is not None :
             uniq_l_ctr, l_ctr_counts = _split_l_ctr_groups(uniq_l_ctr, l_ctr_counts, group_size)
@@ -314,6 +314,7 @@ def build(self, cutoff=1e-14, group_size=None,
             tot_mol._atm.ctypes.data_as(ctypes.c_void_p), ctypes.c_int(tot_mol.natm),
             tot_mol._bas.ctypes.data_as(ctypes.c_void_p), ctypes.c_int(tot_mol.nbas),
             tot_mol._env.ctypes.data_as(ctypes.c_void_p))
+
         cput1 = logger.timer_debug1(tot_mol, 'Initialize GPU cache', *cput1)
         self.bas_pairs_locs = bas_pairs_locs
         ncptype = len(self.log_qs)
@@ -745,29 +746,24 @@ def get_int3c2e_ip1_vjk(intopt, rhoj, rhok, dm0_tag, aoslices, with_k=True, omeg
         vj1_buf[:,i0:i1,j0:j1] += contract('xpji,p->xij', int3c_blk, rhoj[k0:k1])
         # initialize intermediate variables
         if count % ncp_ij == 0:
-            rhoj0 = cupy.zeros([3,k1-k0,nao_sph])
             rhok_tmp = cupy.asarray(rhok[k0:k1])
-            vj1_ao = cupy.zeros([3,nao_sph,nao_sph,nocc])
             if with_k:
                 rhok0_slice = contract('pio,Jo->piJ', rhok_tmp, orbo) * 2
                 rhok0 = contract('pli,lo->poi', rhok0_slice, orbo)
-                int3c_ip1_occ = cupy.zeros([3,k1-k0,nao_sph,nocc])
-                vk1_ao = cupy.zeros([3,nao_sph,nao_sph,nocc])
 
-        # contraction
-        rhoj0[:,:,i0:i1] += contract('xpji,ij->xpi', int3c_blk, dm0_tag[i0:i1,j0:j1])
+        rhoj0 = contract('xpji,ij->xpi', int3c_blk, dm0_tag[i0:i1,j0:j1])
+        vj1_ao = contract('pJo,xpi->xiJo', rhok_tmp, rhoj0)
+        vj1 += 2.0*contract('xiJo,ia->axJo', vj1_ao, ao2atom[i0:i1])
+
         if with_k:
-            int3c_ip1_occ[:,:,i0:i1] += contract('xpji,jo->xpio', int3c_blk, orbo[j0:j1])
-            vk1_ao[:,i0:i1,j0:j1] += contract('xpji,poi->xijo', int3c_blk, rhok0[:,:,i0:i1])
             vk1_buf[:,i0:i1] += contract('xpji,plj->xil', int3c_blk, rhok0_slice[:,:,j0:j1])
 
-        # reduction
-        if (count+1) % ncp_ij == 0:
-            vj1_ao += contract('pjo,xpi->xijo', rhok_tmp, rhoj0)
-            vj1 += 2.0*contract('xiko,ia->axko', vj1_ao, ao2atom)
-            if with_k:
-                vk1_ao += contract('xpio,pki->xiko', int3c_ip1_occ, rhok0_slice)
-                vk1 += contract('xiko,ia->axko', vk1_ao, ao2atom)
+            vk1_ao = contract('xpji,poi->xijo', int3c_blk, rhok0[:,:,i0:i1])
+            vk1[:,:,j0:j1] += contract('xijo,ia->axjo', vk1_ao, ao2atom[i0:i1])
+
+            int3c_ip1_occ = contract('xpji,jo->xpio', int3c_blk, orbo[j0:j1])
+            vk1_ao = contract('xpio,pJi->xiJo', int3c_ip1_occ, rhok0_slice[:,:,i0:i1])
+            vk1 += contract('xiJo,ia->axJo', vk1_ao, ao2atom[i0:i1])
         count += 1
 
     return vj1_buf, vk1_buf, vj1, vk1

gpu4pyscf/dft/libxc.py

@@ -21,7 +21,7 @@
 import cupy
 from pyscf import dft
 
-libxc = np.ctypeslib.load_library(
+_libxc = np.ctypeslib.load_library(
     'libxc', os.path.abspath(os.path.join(__file__, '..', '..', 'lib', 'deps', 'lib')))
 
 def _check_arrays(current_arrays, fields, factor, required):
@@ -45,31 +45,32 @@ class _xcfun(ctypes.Structure):
     pass
 
 _xc_func_p = ctypes.POINTER(_xcfun)
-libxc.xc_func_alloc.restype = _xc_func_p
-libxc.xc_func_init.argtypes = (_xc_func_p, ctypes.c_int, ctypes.c_int)
-libxc.xc_func_end.argtypes = (_xc_func_p, )
-libxc.xc_func_free.argtypes = (_xc_func_p, )
+_libxc.xc_func_alloc.restype = _xc_func_p
+_libxc.xc_func_init.argtypes = (_xc_func_p, ctypes.c_int, ctypes.c_int)
+_libxc.xc_func_end.argtypes = (_xc_func_p, )
+_libxc.xc_func_free.argtypes = (_xc_func_p, )
 
 class XCfun:
     def __init__(self, xc, spin):
         assert spin == 'unpolarized'
         self._spin = 1
-        self.xc_func = libxc.xc_func_alloc()
+        self.xc_func = _libxc.xc_func_alloc()
         if isinstance(xc, str):
-            self.func_id = libxc.xc_functional_get_number(ctypes.c_char_p(xc.encode()))
+            self.func_id = _libxc.xc_functional_get_number(ctypes.c_char_p(xc.encode()))
         else:
             self.func_id = xc
-        ret = libxc.xc_func_init(self.xc_func, self.func_id, self._spin)
+        ret = _libxc.xc_func_init(self.xc_func, self.func_id, self._spin)
         if ret != 0:
             raise RuntimeError('failed to initialize xc fun')
         self._family = dft.libxc.xc_type(xc)
 
     def __del__(self):
         if self.xc_func is None:
             return
-        libxc.xc_func_end(self.xc_func)
-        libxc.xc_func_free(self.xc_func)
-
+        # TODO: deallocate xc func
+        #_libxc.xc_func_end(self.xc_func)
+        #_libxc.xc_func_free(self.xc_func)
+
     def needs_laplacian(self):
         return dft.libxc.needs_laplacian(self.func_id)
 
@@ -85,7 +86,7 @@ def compute(self, inp, output=None, do_exc=True, do_vxc=True, do_fxc=False, do_k
         npoints = int(inp["rho"].size / self._spin)
         if (inp["rho"].size % self._spin):
             raise ValueError("Rho input has an invalid shape, must be divisible by %d" % self._spin)
-        
+
         # Find the right compute function
         args = [self.xc_func, ctypes.c_size_t(npoints)]
         if self._family == 'LDA':
@@ -114,7 +115,7 @@ def compute(self, inp, output=None, do_exc=True, do_vxc=True, do_fxc=False, do_k
                 if(isinstance(arg, cupy.ndarray)):
                     arg = ctypes.cast(arg.data.ptr, ctypes.c_void_p)
                 cuda_args.append(arg)
-            libxc.xc_lda(*cuda_args)
+            _libxc.xc_lda(*cuda_args)
         elif self._family == 'GGA':
             input_labels   = ["rho", "sigma"]
             input_num_args = 2
@@ -141,7 +142,7 @@ def compute(self, inp, output=None, do_exc=True, do_vxc=True, do_fxc=False, do_k
                 if(isinstance(arg, cupy.ndarray)):
                     arg = ctypes.cast(arg.data.ptr, ctypes.c_void_p)
                 cuda_args.append(arg)
-            libxc.xc_gga(*cuda_args)
+            _libxc.xc_gga(*cuda_args)
 
         elif self._family == 'MGGA':
             # Build input args
@@ -178,7 +179,7 @@ def compute(self, inp, output=None, do_exc=True, do_vxc=True, do_fxc=False, do_k
             output = _check_arrays(output, output_labels[5:15], npoints, do_fxc)
             output = _check_arrays(output, output_labels[15:35], npoints, do_kxc)
             output = _check_arrays(output, output_labels[35:70], npoints, do_lxc)
-            
+
             args.extend([   inp[x] for x in  input_labels])
             if not self.needs_laplacian():
                 args.insert(-1, cupy.empty((1)))  # Add none ptr to laplacian
@@ -189,10 +190,10 @@ def compute(self, inp, output=None, do_exc=True, do_vxc=True, do_fxc=False, do_k
                 if(isinstance(arg, cupy.ndarray)):
                     arg = ctypes.cast(arg.data.ptr, ctypes.c_void_p)
                 cuda_args.append(arg)
-            libxc.xc_mgga(*cuda_args)
+            _libxc.xc_mgga(*cuda_args)
         else:
             raise KeyError("Functional kind not recognized!")
-        
+
         return {k: v for k, v in zip(output_labels, args[2+input_num_args:]) if v is not None}