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On the conversion of indirect to direct recursion
ACM Letters on Programming Languages and Systems (LOPLAS)
Power analysis and minimization techniques for embedded DSP software
IEEE Transactions on Very Large Scale Integration (VLSI) Systems
Proper tail recursion and space efficiency
PLDI '98 Proceedings of the ACM SIGPLAN 1998 conference on Programming language design and implementation
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PEPM '00 Proceedings of the 2000 ACM SIGPLAN workshop on Partial evaluation and semantics-based program manipulation
A fully associative software-managed cache design
Proceedings of the 27th annual international symposium on Computer architecture
On-chip vs. off-chip memory: the data partitioning problem in embedded processor-based systems
ACM Transactions on Design Automation of Electronic Systems (TODAES)
Notes on recursion elimination
Communications of the ACM
JouleTrack: a web based tool for software energy profiling
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Dynamic management of scratch-pad memory space
Proceedings of the 38th annual Design Automation Conference
Exploiting scratch-pad memory using Presburger formulas
Proceedings of the 14th international symposium on Systems synthesis
Storage allocation for embedded processors
CASES '01 Proceedings of the 2001 international conference on Compilers, architecture, and synthesis for embedded systems
Heterogeneous memory management for embedded systems
CASES '01 Proceedings of the 2001 international conference on Compilers, architecture, and synthesis for embedded systems
Computer architecture: a quantitative approach
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ACM Transactions on Embedded Computing Systems (TECS)
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Proceedings of the 2003 international conference on Compilers, architecture and synthesis for embedded systems
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Proceedings of the conference on Design, automation and test in Europe - Volume 2
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Dynamic overlay of scratchpad memory for energy minimization
Proceedings of the 2nd IEEE/ACM/IFIP international conference on Hardware/software codesign and system synthesis
A post-compiler approach to scratchpad mapping of code
Proceedings of the 2004 international conference on Compilers, architecture, and synthesis for embedded systems
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WMPI '04 Proceedings of the 3rd workshop on Memory performance issues: in conjunction with the 31st international symposium on computer architecture
Dynamic allocation for scratch-pad memory using compile-time decisions
ACM Transactions on Embedded Computing Systems (TECS)
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Journal of Embedded Computing - Cache exploitation in embedded systems
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IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
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Journal of Computing Sciences in Colleges
Proceedings of the 2011 SIGPLAN/SIGBED conference on Languages, compilers and tools for embedded systems
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LCPC'09 Proceedings of the 22nd international conference on Languages and Compilers for Parallel Computing
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ACM Transactions on Architecture and Code Optimization (TACO) - Special Issue on High-Performance Embedded Architectures and Compilers
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This paper presents the first automatic scheme to allocate local (stack) data in recursive functions to scratch-pad memory (SPM) in embedded systems. A scratch-pad is a fast directly addressed compiler-managed SRAM memory that replaces the hardware-managed cache. It is motivated by its significantly lower access time, energy consumption, real-time bounds, area and overall runtime. Existing compiler methods for allocating data to scratch-pad are able to place only code, global, heap and non-recursive stack data in scratch-pad memory; stack data for recursive functions is allocated entirely in DRAM, resulting in poor performance. In this paper we present a dynamic yet compiler-directed allocation method for recursive function stack data that for the first time, is able to place a portion of recursive stack data in scratch-pad. It has almost no software-caching overhead, and is able to move recursive function data back and forth between scratch-pad and DRAM to better track the program's locality characteristics. With our method, all code, global, stack and heap variables can share the same scratch-pad. When compared to placing all recursive function data in DRAM and all other variables in scratch-pad, our results show that our method reduces the average runtime of our benchmarks by 29.3%, and the average power consumption by 31.1%, for the same size of scratch-pad fixed at5% of total data size. Furthermore,significant savings were observedwhen comparing our method against cache-based alternatives for SPM allocation. Finally, we show results that analyze the effects of profile variation on our allocation approach and present a modified version of our method which minimizes variation for profile-based allocations.