Automatic module allocation in high level synthesis

Gutberlet, P.; Müller, Jörg R.; Kramer, H.

doi:10.1109/eurdac.1992.246223

Cited by 20 publications

(12 citation statements)

References 10 publications

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“…The work in [31] uses "hill climbing" algorithm to optimize number and type of functional unit allocated, while the work in [32] applies clique partitioning in order to minimize storage elements, units, and interconnect. The work in [33] uses the schedule to determine the minimum required number of functional units, buses, register files, and ROMs.…”

Section: Related Workmentioning

confidence: 99%

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Automated Generation of Custom Processor Core from C Code

Trajković

Abdi

Nicolescu

et al. 2012

Journal of Electrical and Computer Engineering

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We present a method for construction of application-specific processor cores from a given C code. Our approach consists of three phases. We start by quantifying the properties of the C code in terms of operation types, available parallelism, and other metrics. We then create an initial data path to exploit the available parallelism. We then apply designer-guided constraints to an interactive data path refinement algorithm that attempts to reduce the number of the most expensive components while meeting the constraints. Our experimental results show that our technique scales very well with the size of the C code. We demonstrate the efficiency of our technique on wide range of applications, from standard academic benchmarks to industrial size examples like the MP3 decoder. Each processor core was constructed and refined in under a minute, allowing the designer to explore several different configurations in much less time than needed for manual design. We compared our selection algorithm to the manual selection in terms of cost/performance and showed that our optimization technique achieves better cost/performance trade-off. We also synthesized our designs with programmable controller and, on average, the refined core have only 23% latency overhead, twice as many block RAMs and 36% fewer slices compared to the respective manual designs.

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Section: Related Workmentioning

confidence: 99%

“…The work in [31][32][33][34][35] separate allocation from binding and scheduling. The work in [31] uses "hill climbing" algorithm to optimize number and type of functional unit allocated, while the work in [32] applies clique partitioning in order to minimize storage elements, units, and interconnect.…”

Section: Related Workmentioning

confidence: 99%

Automated Generation of Custom Processor Core from C Code

Trajković

Abdi

Nicolescu

et al. 2012

Journal of Electrical and Computer Engineering

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show abstract

“…The algorithm is, however, of a nature that makes it applicable in general. To the authors knowledge, no prior work has been done in the area of allocating resources for hardware while considering the consequences for the combined hardware/software system, although several approaches [1,4,5] for allocating resources for an allhardware solution have been proposed. However, in our approach the application is partitioned between software and hardware.…”

Section: Introductionmentioning

confidence: 99%

Hardware resource allocation for hardware/software partitioning in the LYCOS system

Grode¹,

Knudsen²,

Madsen³

Proceedings Design, Automation and Test in Europe

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“…[Gutberlet et al, 1992] uses 'hill climbing' algorithm to optimize number and type of functional unit allocated, while [Tseng and Seiwiorek, 1986] applies clique partitioning in order to minimize storage elements, units and interconnect. [Tsai and Hsu, 1992] use the schedule to determine the minimum required number of functional units, buses, register files and ROMs.…”

Section: Related Workmentioning

confidence: 99%

“…[ Gutberlet et al, 1992;Tseng and Seiwiorek, 1986;Tsai and Hsu, 1992;Brewer and Gajski, 1990;Marwedel, 1993] separate allocation from binding and scheduling. [Gutberlet et al, 1992] uses 'hill climbing' algorithm to optimize number and type of functional unit allocated, while [Tseng and Seiwiorek, 1986] applies clique partitioning in order to minimize storage elements, units and interconnect.…”

Section: Related Workmentioning

confidence: 99%

Automatic Data Path Generation from C code for Custom Processors

Trajković

Gajski

IFIP – The International Federation for Information Processing

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Abstract:The stringent performance constraints and short time to market of modern digital systems require automatic methods for design of high performance applicationspecific architectures. This paper presents a novel algorithm for automatic generation of custom pipelined data path for a given application from its C code. The data path optimization targets both resource utilization and performance. The input to this architecture generator includes application C code, operation execution frequencies obtained by the profile run and a component library consisting of functional units, busses, multiplexers etc. The output is data path specified as a net-list of resource instances and their connections. The algorithm starts with an architecture that supports maximum parallelism for implementation of the input C code and iteratively refines it until an efficient resource utilization is obtained while maintaining the performance constraint. This paper also presents an algorithm to choose the priority of application basic blocks for optimization. Our experimental results show that automatically generated data paths satisfy given performance criteria and can be obtained in a matter of minutes leading to significant productivity gains.

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Automatic module allocation in high level synthesis

Cited by 20 publications

References 10 publications

Automated Generation of Custom Processor Core from C Code

Automated Generation of Custom Processor Core from C Code

Hardware resource allocation for hardware/software partitioning in the LYCOS system

Automatic Data Path Generation from C code for Custom Processors

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