Some beginner problems

[steto123]

After succesfully installing cuda, gpu4pscf und cutensor in my jupyter environment on my university hpc cluster i have problems running examples:

/home/sthomas/.conda/envs/myjupyter/lib/python3.10/site-packages/cupy/_environment.py:370: UserWarning: CuPy failed to preload library (/home/sthomas/.conda/envs/myjupyter/lib/python3.10/site-packages/cutensor/lib/libcutensor.so.2): OSError (libcublasLt.so.12: cannot open shared object file: No such file or directory) warnings.warn(msg) /home/sthomas/.conda/envs/myjupyter/lib/python3.10/site-packages/gpu4pyscf/lib/cutensor.py:138: UserWarning: using cupy as the tensor contraction engine. warnings.warn(f'using {contract_engine} as the tensor contraction engine.')

NVRTCError Traceback (most recent call last) File ~/.conda/envs/myjupyter/lib/python3.10/site-packages/cupy/cuda/compiler.py:692, in _NVRTCProgram.compile(self, options, log_stream) 691 nvrtc.addNameExpression(self.ptr, ker) --> 692 nvrtc.compileProgram(self.ptr, options) 693 mapping = None

File cupy_backends/cuda/libs/nvrtc.pyx:125, in cupy_backends.cuda.libs.nvrtc.compileProgram()

File cupy_backends/cuda/libs/nvrtc.pyx:138, in cupy_backends.cuda.libs.nvrtc.compileProgram()

File cupy_backends/cuda/libs/nvrtc.pyx:53, in cupy_backends.cuda.libs.nvrtc.check_status()

NVRTCError: NVRTC_ERROR_COMPILATION (6)

During handling of the above exception, another exception occurred:

CompileException Traceback (most recent call last)

... (the full error listing is attached)

pip show cutensor-cu12 shows only one version of cutensor installed

---

alternatively i have started compiling gpu4pyscf.

After solving some little problems compiling stops:

[ 63%] Completed 'libxc' [ 66%] Built target libxc gmake: *** [Makefile:91: all] Error 2

Does anyone have some good ideas for me?

Thank you

errors.txt

[wxj6000]

It seems that nvrtc is missing in your CUDA environment. You can try to add it when you install cuda-toolkit (it is a part of cuda-toolkit).

[steto123]

Many thanks for your help.

I was able to use the precompiled cuda11x versions in a clean environment on our HPC Cluster without greater problems.

Many thanks

And another question:

Is there an example for calculating shieldings? I found test_shielding.py but i do not have an ide how to integrate this in a optimisation run. (for pyscf i found a simple example and i will inspect this in the next days more intense)

[sunqm]

In current version, you can run

from gpu4pyscf.properties.shielding import eval_shielding
mf = mol.RKS().to_gpu().run()
eval_shielding(mf)

[steto123]

Many thanks for your time to answer me. I have used this in the following example:

` xyzin="propanol-g_opt1.xyz" # funktioniert logfile="test_g.log"

import gpu4pyscf from gpu4pyscf.properties.shielding import eval_shielding mol = pyscf.M(atom=xyzin, basis='6-31g*', output=logfile)

#mf = dft.RKS(mol) #mf.xc = 'b3lyp'

mf = mol.RKS().to_gpu().run() eval_shielding(mf)

`

i have uncommented the two lines alone and both at the same time. In all cases the error was the following:

---

ValueError Traceback (most recent call last) Cell In[8], line 21 17 mf.xc = 'b3lyp' 20 mf = mol.RKS().to_gpu().run() ---> 21 eval_shielding(mf)

File ~/miniconda3/lib/python3.12/site-packages/gpu4pyscf/properties/shielding.py:205, in eval_shielding(mf) 202 dm0 = mf.make_rdm1() 203 natom = mf.mol.natm --> 205 h1ao = get_h1ao(mf) 206 tmp = contract('xuv,ua->xav', s1ao, mvir) 207 s1ai = contract('xav,vi->xai', tmp, mocc)

File ~/miniconda3/lib/python3.12/site-packages/gpu4pyscf/properties/shielding.py:180, in get_h1ao(mf) 178 h1ao += -mf.mol.intor('int1e_ignuc') 179 h1ao = cupy.array(h1ao) --> 180 h1ao += get_vxc(mf, dm0) 182 return h1ao

File ~/miniconda3/lib/python3.12/site-packages/gpu4pyscf/properties/shielding.py:160, in get_vxc(mf, dm0) 159 def get_vxc(mf, dm0): --> 160 vxc = nr_rks(mf._numint, mf.mol, mf.grids, mf.xc, mf.make_rdm1()) 161 # ! imaginary part 162 vj, vk = get_jk(mf.mol, dm0)

File ~/miniconda3/lib/python3.12/site-packages/gpu4pyscf/properties/shielding.py:100, in nr_rks(ni, mol, grids, xc_code, dms) 98 giao_aux = giao[:,:,index] 99 for idirect in range(3): --> 100 vtmp = contract('pu,p,vp->uv', giao_aux[idirect], wv, ao) 101 vtmp = cupy.ascontiguousarray(vtmp) 102 add_sparse(vmat[idirect], vtmp, index)

File ~/miniconda3/lib/python3.12/site-packages/gpu4pyscf/lib/cutensor.py:151, in contract(pattern, a, b, alpha, beta, out) 146 def contract(pattern, a, b, alpha=1.0, beta=0.0, out=None): 147 ''' 148 a wrapper for general tensor contraction 149 pattern has to be a standard einsum notation 150 ''' --> 151 return contraction(pattern, a, b, alpha, beta, out=out)

File ~/miniconda3/lib/python3.12/site-packages/gpu4pyscf/lib/cutensor.py:73, in contraction(pattern, a, b, alpha, beta, out, op_a, op_b, op_c, algo, jit_mode, compute_desc, ws_pref) 60 def contraction( 61 pattern, a, b, alpha, beta, 62 out=None, (...) 69 ws_pref=WORKSPACE_RECOMMENDED 70 ): 72 pattern = pattern.replace(" ", "") ---> 73 str_a, rest = pattern.split(',') 74 str_b, str_c = rest.split('->') 75 key = str_a + str_b

ValueError: too many values to unpack (expected 2)

This makes me unhappy. Can you help me again?

Many thanks for your work and help.

[wxj6000]

This is a bug when you use LDA functional for NMR shielding calculation. It has been fixed in https://github.com/pyscf/gpu4pyscf/pull/256

Just a reminder. These modules (Polarizability, IR, and NMR shielding) are still experimental. They probably are not as efficient as SCF module.

[steto123]

Many thanks for your help and this reminder. I have editited shielding.py in the same way and now it works.

Steffen