Complete student projects
- Johnston, B, Falzon, G & Milthorpe, J 2018, 'OpenCL performance prediction using architecture-independent features', 16th International Conference on High Performance Computing and Simulation, HPCS 2018, ed. K Zine-Dine & W Smari, IEEE, United States, pp. 561-569pp.
- Johnston, B & Milthorpe, J 2018, 'AIWC: OpenCL-Based architecture-independent workload characterization', 5th IEEE/ACM Workshop on the LLVM Compiler Infrastructure in HPC, LLVM-HPC 2018, IEEE, Piscataway, United States, pp. 81-91pp.
- Johnston, B & Milthorpe, J 2018, 'Dwarfs on accelerators: Enhancing OpenCL benchmarking for heterogeneous computing architectures', Proceedings of the 47th International Conference on Parallel Processing Companion. [hide] 
- Johnston, B, Lee, C, Angove, L et al 2017, 'Embedded Accelerators for Scientific High-Performance Computing: An Energy Study of OpenCL Gaussian Elimination Workloads', 46th International Conference on Parallel Processing Workshops, ICPPW 2017, ed. Randall Bilof, IEEE, TBC, pp. 59-68.
- Johnston, B & McCreath, E 2017, 'Parallel huffman decoding: presenting a fast and scalable algorithm for increasingly multicore devices', 15th IEEE International Symposium on Parallel and Distributed Processing with Applications and 16th IEEE International Conference on Ubiquitous Computing and Communications, ISPA/IUCC 2017, ed. Guojun Wang, Geoffrey Fox, Gregorio Martinez, Richard Hill and Peter Mueller, IEEE, TBC, pp. 949-958.
- Gaurav Mitra, Beau Johnston, Eric C. McCreath, Jun Zhou, and Alistair P. Rendell, 2013 'Use of SIMD Vector Operations to Accelerate Application Code Performance on Low-Powered ARM and Intel Platforms', 2013 IEEE 27th International Symposium on Parallel & Distributed Processing Workshops and PhD Forum (IPDPSW), IEEE Computer Society, New York USA, pp. 1107 - 1116.