Implementations of hardware acceleration for MD4-family algorithms based on GPU
ASID'09 Proceedings of the 3rd international conference on Anti-Counterfeiting, security, and identification in communication
Exploring the concurrency of an MPEG RVC decoder based on dataflow program analysis
IEEE Transactions on Circuits and Systems for Video Technology
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Hi-index | 0.00 |
Multi-core processors represent a major development in computing technology. For example, Intel® Core™ 2 Quad processors, IBM Cell processors, and Nvidia GeForce 9800 GX2, are widely used. However, most applications struggle to make the best use of the power provided by many-core processors. Easy-to-use software tools are hard to find. Furthermore, it's not clear what changes need to be made to algorithms to fully utilize many-core CPUs or GPUs. In this paper, we try to offer a bird's eye view of the opportunities lying ahead in two folds: (1) software tools and (2) workload analysis. With good software tools and insightful workload analysis, software and algorithm developers can not only harness the power of many computing cores, but also innovate new algorithms that best utilize the many computing cores. New algorithms and applications are thus made possible with the computing power not available before.