Application of splay trees to data compression
Communications of the ACM
DDJ Data Compression Contest results
Dr. Dobb's Journal
The data compression book (2nd ed.)
The data compression book (2nd ed.)
Wattch: a framework for architectural-level power analysis and optimizations
Proceedings of the 27th annual international symposium on Computer architecture
IEEE Transactions on Computers
XTREM: a power simulator for the Intel XScale® core
Proceedings of the 2004 ACM SIGPLAN/SIGBED conference on Languages, compilers, and tools for embedded systems
A Survey on Data Compression in Wireless Sensor Networks
ITCC '05 Proceedings of the International Conference on Information Technology: Coding and Computing (ITCC'05) - Volume II - Volume 02
Energy-aware lossless data compression
ACM Transactions on Computer Systems (TOCS)
Data compression algorithms for energy-constrained devices in delay tolerant networks
Proceedings of the 4th international conference on Embedded networked sensor systems
Profiling of symmetric-encryption algorithms for a novel biomedical-implant architecture
Proceedings of the 5th conference on Computing frontiers
Prius: generic hybrid trace compression for wireless sensor networks
Proceedings of the 10th ACM Conference on Embedded Network Sensor Systems
| Hi-index | 0.00 |
In view of a booming market for microelectronic implants, our ongoing research work is focusing on the specification and design of a novel biomedical microprocessor core targeting a large subset of existing and future biomedical applications. Towards this end, we have taken steps in identifying various tasks commonly required by such applications and profiling their behavior and requirements. A prominent family of such tasks is lossless data compression. In this work we profile a large collection of compression algorithms on suitably selected biomedical workloads. Compression ratio, average and peak power consumption, total energy budget, compression rate and program-code size metrics have been evaluated. Findings indicate the best-performing algorithms across most metrics to be mlzo (scores high in 5 out of 6 imposed metrics) and fin (present in 4 out of 6 metrics). Further mlzo profiling reveals the dominance of i) address-generation, load, branch and compare instructions, and ii) interdependent logical-logical and logical-compare instructions combinations.