The performance of parallel distributed file systems suffers from many clients executing a large number of operations in parallel, because the I/O subsystem can be easily overwhelmed by the sheer amount of incoming I/O operations. Many optimizations exist that try to alleviate this problem. Client-side optimizations perform preprocessing to minimize the amount of work the file servers have to do. Server-side optimizations use server-internal knowledge to improve performance. The HD Trace framework contains components to simulate, trace and visualize applications. It is used as a test bed to evaluate optimizations that could later be implemented in real-life projects. This paper compares existing client-side optimizations and newly implemented server-side optimizations and evaluates their usefulness for I/O patterns commonly found in HPC. Server-directed I/O chooses the order of non-contiguous I/O operations and tries to aggregate as many operations as possible to decrease the load on the I/O subsystem and improve overall performance. The results show that server-side optimizations beat client-side optimizations in terms of performance for many use cases. Integrating such optimizations into parallel distributed file systems could alleviate the need for sophisticated client-side optimizations. Due to their additional knowledge of internal workflows server-side optimizations may be better suited to provide high performance in general.