IHEP is a multi-disciplinary research institution which is hosting or attending about 15 experiments in the field of high energy physics, including LHAASO, BES, JUNO, HEPS, DYW, ALI, GECAM, ATLAS, CMS, LHCb, etc[1]. Corresponding to these diverse experiments, also in the computing system, a range of usage scenarios has to be considered and the technologies employed should be suitable for the different requirements from these experiments and applications. The technological architectures and the corresponding scenarios are: 1. a local sharing pool for massive offline data processing; 2. a unified sharing pool with a special resource policy for WLCG (Worldwide LHC Computing Grid) and JUNO distributed computing grid; 3. a dHTC (distributed High Throughput Computing) pool for resources sharing between HTC (High Throughput Computing) and HPC (High Performance Computing) and between sites; 4. a near-real-time computing pool for astrophysics streaming data processing; 5. customized clusters for the cooperating institutions or universities. HTCondor[2] is a popular distributed batch system in HEP computing. This paper will discuss an HTC computing system supporting different usage scenarios, based on HTCondor at IHEP, including local batch computing, distributed computing and near-real-time computing. Currently, the whole computing system is managing about 50,000 CPU cores (including x86-arch CPU and arm-arch CPU) and some GPU cards.