Scalability of a Parallel JPEG Encoder on Shared Memory Architectures

Embedded multimedia systems are expected to fully embrace the future many-core wave. As a consequence parallel programming is being revamped as the only way to exploit the power of coming chips. While waiting for them we try to extrapolate some lessons learned from current multi-cores to influence future architectures and programming methods. In this paper we investigate the parallelism and scalability of a JPEG image encoder, which is a typical embedded application, on several shared memory machines using the OpenMP programming framework. We identify the Huffman coding as the bottleneck that blocks the application from scaling above a 7x factor. We propose a strategy to parallelize the Huffman coding, which introduces a small degradation in some parts of the image, allowing to reach higher speedup factors. A factor of 18.8x has been reached in SGI Altix 4700 using 22 threads. Contrasting these results with some previous works using message passing architectures we consider that the use of OpenMP on top of shared memory architectures should be reconsidered for future chips in favor of message passing architectures and programming models.