Skip to Main Content
Compression and encryption applications are important components of modern multimedia workloads. These workloads are typically executed on application specific integrated circuits (ASICs), application specific processors (ASPs), or general purpose processors (GPPs). GPPs are flexible and allow changes in the applications and algorithms better than ASICs and ASPs. However, executing these applications on GPPs is done at a high cost. In this paper, we analyze media compression and encryption applications from the perspective of executing them on a programmable general purpose processor versus ASPs. We select 12 programs from various types of compression and encryption applications. The instruction mix, data types of memory operations, and memory access workloads during the execution of these programs are analyzed. Most of these applications involve processing the data through execution phases (e.g., quantization, encoding, etc.) and temporary results are stored and retrieved between these phases. A metric called overhead memory-access bandwidth per input and output byte is defined to characterize the temporary storage and retrieval of data during execution. We observe that more than 90 percent of the memory accesses made by these programs are temporary data stores and loads arising from the general purpose nature of the execution platform. We also verify the robustness of the proposed metric on different experimental environments using various input data properties and compiler optimizations.