A Virtual Machine (VM) scheduler for homogeneous High Performance Computing (HPC) cloud environments is presented in this paper. This scheduler considers each VM workload type (CPU or I/O-bound) to decide on its allocation. Scheduler is able to reduce energy consumption, as well as SLA violations on this cloud environment, avoiding performance losses by allocating simultaneously VMs which run different types of tasks.The scheduler method was validated through simulations conducted with the CloudSim framework. Two synthetic benchmarks representing both workload types were run previously in VMs in order to obtain basic data to design the scheduler. Thus, it was possible to implement a scheduling method that employs a VM allocation policy based on features of each application. Results showed that knowing the specifications and characteristics of environment may contribute to a better usage of resources, leading to an increased level of services availability and, finally, reducing problems caused by competition in resource usage.