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Garp: a MIPS processor with a reconfigurable coprocessor
Abstract
Typical reconfigurable machines exhibit shortcomings that make them less than ideal for general-purpose computing. The Garp Architecture combines reconfigurable hardware with a standard MIPS processor on the same die to retain the better features of both. Novel aspects of the architecture are presented, as well as a prototype software environment and preliminary performance results. Compared to an UltraSPARC, a Garp of similar technology could achieve speedups ranging from a factor of 2 to as high as a factor of 24 for some useful applications.
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Cited by
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Chen, Y.-H., Emer, J., & Sze, V. (2016) · ACM SIGARCH Computer Architecture News · doi:10.1145/3007787.3001177 · Cited by 1,182
An asymmetric distributed shared memory model for heterogeneous parallel systems
Gelado, I., Stone, J. E., Cabezas, J., Patel, S., Navarro, N., & Hwu, W.-M. W. (2010) · ACM SIGARCH Computer Architecture News · doi:10.1145/1735970.1736059 · Cited by 25
Metadata
- Authors
- Hauser, J. R., & Wawrzynek, J.
- Venue
- Proceedings. The 5th Annual IEEE Symposium on Field-Programmable Custom Computing Machines Cat. No.97TB100186)
- Publisher
- IEEE Comput. Soc
- Published
- 2002-11-23
- Pages
- 12-21
- OpenAlex
- W2165099691
- Cited by
- 792
- References
- 0
- FWCI
- 52.12
- Type
- conference paper
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: Garp: a MIPS processor with a reconfigurable coprocessor. https://app.cochat.ai/papers/10.1109/fpga.1997.624600
- The paper
- Hauser, J. R., & Wawrzynek, J. (2002). Garp: a MIPS processor with a reconfigurable coprocessor. Proceedings. The 5th Annual IEEE Symposium on Field-Programmable Custom Computing Machines Cat. No.97TB100186). https://doi.org/10.1109/fpga.1997.624600
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
