Symbolic execution (SE) has been widely adopted for automatic program analysis and software testing. Many SE engines (e.g., KLEE or Angr) need to interpret certain intermediate representations (IR) of code during execution, which may be slow and costly. Although a plurality of studies is proposed to accelerate SE, few of them consider optimizing the internal interpretation operations. In this paper, we propose FastKLEE, a faster SE engine that aims to speed up execution via reducing redundant bound checking of type-safe pointers during IR code interpretation. Our two key insights are: (1) the number of interpreted instructions can be tremendous and reducing the interpretation overheads of the extensively interpreted ones (e.g., read/write) could potentially accelerate the execution; (2) a large portion of the pointers in C programs can be statically verified to be type-safe but existing SE engines treat all the pointers equally, meaning that those engines perform unnecessary bound checking for all the pointers, thus slowing down the execution. Specifically, in FastKLEE, a type inference system is first leveraged to classify pointer types (i.e., safe or unsafe) for the most frequently interpreted read/write instructions. Then, a customized memory operation is designed to perform bound checking for only the unsafe pointers and omit redundant checking on safe pointers during interpretation. We implement FastKLEE on top of the well-known SE engine KLEE and combined it with the notable type inference system CCured. Evaluation results demonstrate that FastKLEE is able to reduce by up to 9.1% (5.6% on average) as the state-of-the-art approach KLEE in terms of the time to explore the same number (i.e., 10k) of execution paths. FastKLEE is open-sourced at https://github.com/haoxintu/FastKLEE. A video demo of FastKLEE is available at https://youtu.be/fjV_a3kt-mo.