The DOI matches its Crossref record; 23 of the 23 references it cites were found in a registry or an index.
Larrabee: a many-core x86 architecture for visual computing
Abstract
This paper presents a many-core visual computing architecture code named Larrabee, a new software rendering pipeline, a manycore programming model, and performance analysis for several applications. Larrabee uses multiple in-order x86 CPU cores that are augmented by a wide vector processor unit, as well as some fixed function logic blocks. This provides dramatically higher performance per watt and per unit of area than out-of-order CPUs on highly parallel workloads. It also greatly increases the flexibility and programmability of the architecture as compared to standard GPUs. A coherent on-die 2 nd level cache allows efficient inter-processor communication and high-bandwidth local data access by CPU cores. Task scheduling is performed entirely with software in Larrabee, rather than in fixed function logic. The customizable software graphics rendering pipeline for this architecture uses binning in order to reduce required memory bandwidth, minimize lock contention, and increase opportunities for parallelism relative to standard GPUs. The Larrabee native programming model supports a variety of highly parallel applications that use irregular data structures. Performance analysis on those applications demonstrates Larrabee's potential for a broad range of parallel computation.
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Cites
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Debunking the 100X GPU vs. CPU myth: an evaluation of throughput computing on CPU and GPU
Lee, V. W., Kim, C., Chhugani, J., Deisher, M., Kim, D., Nguyen, A. D., Satish, N., Smelyanskiy, M., Chennupaty, S., Hammarlund, P., et al. (2010) · Proceedings of the 37th annual international symposium on Computer architecture · doi:10.1145/1815961.1816021 · Cited by 640
Self-citationPyCUDA and PyOpenCL: A scripting-based approach to GPU run-time code generation
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Towards dense linear algebra for hybrid GPU accelerated manycore systems
Tomov, S., Dongarra, J., & Baboulin, M. (2010) · Parallel Computing · doi:10.1016/j.parco.2009.12.005 · Cited by 451
Graphics processing unit (GPU) programming strategies and trends in GPU computing
Brodtkorb, A. R., Hagen, T. R., & Sætra, M. L. (2013) · Journal of Parallel and Distributed Computing · doi:10.1016/j.jpdc.2012.04.003 · Cited by 283
Metadata
- Authors
- Seiler, L., Carmean, D., Sprangle, E., Forsyth, T., Abrash, M., Dubey, P., Junkins, S., Lake, A., Sugerman, J., Cavin, R., Espasa, R., Grochowski, E., Juan, T., & Hanrahan, P.
- Venue
- ACM Transactions on Graphics
- Published
- 2008-08
- Volume
- 27
- Issue
- 3
- Pages
- 1-15
- ISSN
- 0730-0301 (ISSN-L)
- 1557-7368
- OpenAlex
- W2169150396
- Cited by
- 771
- References
- 23
- FWCI
- 325.00
- Type
- journal article
- Language
- en
- Open access
- closed
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- Seiler, L., Carmean, D., Sprangle, E., Forsyth, T., Abrash, M., Dubey, P., Junkins, S., Lake, A., Sugerman, J., Cavin, R., Espasa, R., Grochowski, E., Juan, T., & Hanrahan, P. (2008). Larrabee: a many-core x86 architecture for visual computing. ACM Transactions on Graphics. https://doi.org/10.1145/1360612.1360617
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