Compilers: principles, techniques, and tools
Compilers: principles, techniques, and tools
On-chip vs. off-chip memory: the data partitioning problem in embedded processor-based systems
ACM Transactions on Design Automation of Electronic Systems (TODAES)
Dynamic management of scratch-pad memory space
Proceedings of the 38th annual Design Automation Conference
Compiler-directed scratch pad memory hierarchy design and management
Proceedings of the 39th annual Design Automation Conference
Scratchpad memory: design alternative for cache on-chip memory in embedded systems
Proceedings of the tenth international symposium on Hardware/software codesign
An integrated hardware/software approach for run-time scratchpad management
Proceedings of the 41st annual Design Automation Conference
On-chip Stack Based Memory Organization for Low Power Embedded Architectures
DATE '03 Proceedings of the conference on Design, Automation and Test in Europe - Volume 1
A post-compiler approach to scratchpad mapping of code
Proceedings of the 2004 international conference on Compilers, architecture, and synthesis for embedded systems
Memory allocation for embedded systems with a compile-time-unknown scratch-pad size
Proceedings of the 2005 international conference on Compilers, architectures and synthesis for embedded systems
Memory Coloring: A Compiler Approach for Scratchpad Memory Management
Proceedings of the 14th International Conference on Parallel Architectures and Compilation Techniques
A novel instruction scratchpad memory optimization method based on concomitance metric
ASP-DAC '06 Proceedings of the 2006 Asia and South Pacific Design Automation Conference
MiBench: A free, commercially representative embedded benchmark suite
WWC '01 Proceedings of the Workload Characterization, 2001. WWC-4. 2001 IEEE International Workshop
Dynamic allocation for scratch-pad memory using compile-time decisions
ACM Transactions on Embedded Computing Systems (TECS)
A dynamic code placement technique for scratchpad memory using postpass optimization
CASES '06 Proceedings of the 2006 international conference on Compilers, architecture and synthesis for embedded systems
Heap data allocation to scratch-pad memory in embedded systems
Journal of Embedded Computing - Cache exploitation in embedded systems
A novel technique to use scratch-pad memory for stack management
Proceedings of the conference on Design, automation and test in Europe
Efficient dynamic heap allocation of scratch-pad memory
Proceedings of the 7th international symposium on Memory management
A software-only solution to use scratch pads for stack data
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Heap data management for limited local memory (LLM) multi-core processors
CODES/ISSS '10 Proceedings of the eighth IEEE/ACM/IFIP international conference on Hardware/software codesign and system synthesis
Vector class on limited local memory (LLM) multi-core processors
CASES '11 Proceedings of the 14th international conference on Compilers, architectures and synthesis for embedded systems
Stack data management for Limited Local Memory (LLM) multi-core processors
ASAP '11 Proceedings of the ASAP 2011 - 22nd IEEE International Conference on Application-specific Systems, Architectures and Processors
Automatic and efficient heap data management for limited local memory multicore architectures
Proceedings of the Conference on Design, Automation and Test in Europe
CMSM: an efficient and effective code management for software managed multicores
Proceedings of the Ninth IEEE/ACM/IFIP International Conference on Hardware/Software Codesign and System Synthesis
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Software Managed Multicore (SMM) architectures have been proposed as a solution for scaling the memory architecture. In an SMM architecture, there are no caches, and each core has only a local scratchpad memory. If all the code and data of the task to be executed on an SMM core cannot fit on the local memory, then data must be managed explicitly in the program through DMA instructions. While all code and data need to be managed, an efficient technique to manage stack data is of utmost importance since an average of 64% of all accesses may be to stack variables [16]. In this paper, we formulate the problem of stack data management optimization on an SMM core. We then develop both an ILP and a heuristic - SSDM (Smart Stack Data Management) to find out where to insert stack data management calls in the program. Experimental results demonstrate SSDM can reduce the overhead by 13X over the state-of-the-art stack data management technique [10].