Executing compressed programs on an embedded RISC architecture
MICRO 25 Proceedings of the 25th annual international symposium on Microarchitecture
Tile size selection using cache organization and data layout
PLDI '95 Proceedings of the ACM SIGPLAN 1995 conference on Programming language design and implementation
Enhanced code compression for embedded RISC processors
Proceedings of the ACM SIGPLAN 1999 conference on Programming language design and implementation
Effective algorithms for cache-level compression
GLSVLSI '01 Proceedings of the 11th Great Lakes symposium on VLSI
Hardware Compressed Main Memory: Operating System Support and Performance Evaluation
IEEE Transactions on Computers
Profile-guided code compression
PLDI '02 Proceedings of the ACM SIGPLAN 2002 Conference on Programming language design and implementation
High Performance Compilers for Parallel Computing
High Performance Compilers for Parallel Computing
Code compression for VLIW processors using variable-to-fixed coding
Proceedings of the 15th international symposium on System Synthesis
Design and Evaluation of a Selective Compressed Memory System
ICCD '99 Proceedings of the 1999 IEEE International Conference on Computer Design
Hardware-Assisted Data Compression for Energy Minimization in Systems with Embedded Processors
Proceedings of the conference on Design, automation and test in Europe
LZW-Based Code Compression for VLIW Embedded Systems
Proceedings of the conference on Design, automation and test in Europe - Volume 3
Code Compression Based on Operand-Factorization for VLIW Processors
DCC '04 Proceedings of the Conference on Data Compression
Profile-Driven Selective Code Compression
DATE '03 Proceedings of the conference on Design, Automation and Test in Europe - Volume 1
ILP-Based energy minimization techniques for banked memories
ACM Transactions on Design Automation of Electronic Systems (TODAES)
Using data compression for increasing memory system utilization
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
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Memory system presents one of the critical challenges on embedded system design and optimization. This is mainly due to ever-increasing code complexity of embedded applications and exponential increase witnessed in the amount of data they manipulate. As a result, reducing memory space occupancy of embedded applications is very important and will be even more important in the next decade. Motivated by this observation, this paper presents and evaluates a compiler-driven approach to data compression for reducing memory space occupancy. Our goal in this paper is to study how automated compiler support can help in deciding the set of data elements to compress/decompress and the points during execution at which these compressions/decompressions should be performed. The proposed compiler support achieves this by analyzing the source code of the application to be optimized and identifying the order in which the different data blocks are accessed. Based on this analysis, the compiler then automatically inserts compression/decompression calls in the application code. The compression calls target the data blocks that are not expected to be used in the near future, whereas the decompression calls target those data blocks with expected reuse but currently in compressed form.