Compiler optimizations intend to transform a program into a semantic-equivalent one with improved performance, but it is unclear how these optimizations may impact the performance of dynamic symbolic execution (DSE) on binary code. To systematically understand the impact of compiler optimizations on two popular DSE techniques (i.e., symbolic exploration and symbolic tracing), this paper presents an empirical study that quantifies 209 GCC compilation flags and 73 Clang compilation flags to reveal both positive and negative optimizations to DSE. Our data set contains 992 unique test cases, which are produced from 3,449 source files in the GCC test suite. After analyzing 2,978,976 binary programs that we compiled with two compilers and various compilation flags, we found that although some optimizations make DSE faster, most optimizations will actually slow down DSE. Our analysis further reveals root causes behind these impacts. The most positive impacts that optimizations have on DSE come from the reduction of the number of instructions and program paths, whereas negative impacts are caused by a series of unexpected behaviors, including increased numbers of instructions or program paths, library function inlining preventing DSE engines from using function summaries, and arithmetic optimizations leading to more sophisticated constraints. Being the first in-depth analysis on why compiler flags influence the performance of DSE, this project sheds light on program transformations that can be applied before performing DSE tasks for better performance.