CryoEM Packages =============================================================================== Update (2023-06-26) The conda environment (and package) name now follows: "cryoem-$ARCH_$SUBARCH-r$RELION_VERSION_cuda$CUDA_SM_VERSION-c$CTFFIND_VERSION-p$ENV_PYTHON_VERSION-$OS_VERSION.tar.$COMPRESSION_ALG" Only one package was built during this release: - cryoem-ppc64le_p9-r4.0.1_cuda3.5-c4.1.14-p3.10.11-ub_2004.tar.gz - RELION 4.0.1, CUDA cabability 3.5 - CTFFIND 4.1.14 - Python 3.10.11 - Ubuntu 20.04.6 LTS (Focal Fossa) - cryoem-ppc64le_p9-r4.0.1_cuda7.0-c4.1.14-p3.10.11-ub_2004.tar.gz - RELION 4.0.1, CUDA cabability 7.0 - CTFFIND 4.1.14 - Python 3.10.11 - Ubuntu 20.04.6 LTS (Focal Fossa) =============================================================================== Update (2022-09-21) Choose the CryoEM tar file that corresponds to your architecture (ppc64le), your Python version (Python3.10.6 or Python3.10.4), your version of relion (3.1.3 or 4.0beta), operating system (U20.04 was compile on Ubuntu 20.04, RH7.9 was compiled on Centos 7.9) and a compatible SM version (35 or 70). For SM version, see https://developer.nvidia.com/cuda-gpus#compute Use the Compute Apability number without decimal point (3.5 = 35, 7.0 = 70) corresponding to your card from the tables on that page.