Gang scheduling, has long been adopted by the high-performance computing community as a way to reduce the synchronization overhead between related threads. Gang schedulling allows for several threads to execute in lock steps without suffering from long busy-wait periods or be penalised by large context-switch overheads. If several threads use the same data, it also reduces the number of memory transactions by allowing the program to load those data only once for all threads rather than once per thread. To avoid reloading large amount of data after each preemption and hence incur large execution-time overheads, in this work, we assume that the tasks adhere to a limited-preemptive execution model. We further assume that each gang task is moldable, that is, it has a minimum and a maximum number of cores on which it may be executed. The actual execution time of a job depends then on the number of cores allocated by the scheduler at run-tiem. In this work, we consider the case for which tasks are scheduled according to a global job-level fixed priority scheduling algorithm, and present a worst-case response time analysis for limited-preemptive moldable gang tasks. Additionally, we propose a new scheduling policy to improve the schedulability of moldable gang tasks.