Recently, a number of researchers have started to investigate new video-on-demand (VoD) architectures using batching, patching and periodic broadcasting. These architectures, compared to traditional unicast VoD systems, are much more scalable and can serve thousands or even millions of clients concurrently. Nevertheless, existing studies are usually focused on architectural issues. The problem of designing an efficient server to implement these new multicast VoD architectures has received little attention. While existing server designs using round-based schedulers can still be used, results show that such designs are sub-optimal as they do not exploit the characteristics of fixed-schedule periodic broadcasting channels. This study addresses this challenge by presenting an efficient server design for a recent multicast VoD architecture called Super-Scalar Video-on-Demand (SS-VoD). Results show that the efficient server design can increase the system capacity by 60% compared to traditional video server designs. This paper presents details of this new server design, derives a performance model, and analyzes it using numerical results.Recently, Lee and Lee [2] proposed a Super-Scalar video-on-demand (SS-VoD) architecture combining the virtues of batching, patching, and periodic broadcasting for implementing scalable and efficient VoD services. In a SS-VoD system, multicast channels are divided into two types -static channels and dynamic channels. Each channel transmits video data at the video playback rate using network multicast. Static channels are organized in a time-staggered manner to stream the whole video repeatedly and periodically. Dynamic channels are scheduled with batching and patching to enable clients to begin playback quickly. By simultaneously caching data from a static channel, the client can eventually merge back to an existing static channel and release the