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====== Rodinia: Accelerating Compute-Intensive Applications with Accelerators ======
A vision of heterogeneous computer systems that incorporate diverse accelerators and automatically select the best 
computational unit for a particular task is widely shared among researchers and many industry analysts; however, 
there are no agreed-upon benchmarks to support the research needed in the development of such a platform. There 
are many suites for parallel computing on general-purpose CPU architectures, but accelerators fall into a gap that is 
not covered by previous benchmark development. Rodinia is released to address this concern.

The Rodinia Benchmark Suite, version 3.1 ([[https://web.archive.org/web/20180227025117/http://www.cs.virginia.edu:80/~skadron/wiki/rodinia/index.php/TechnicalDoc|Version history]])
Rodinia is designed for heterogeneous computing infrastructures with OpenMP, OpenCL and CUDA implementations.

^ Applications    ^ Dwarves       ^ Domains         ^Parallel Model         ^Incre. Ver. ^
|[[Leukocyte|Leukocyte]]|Structured Grid|Medical Imaging|CUDA, OMP, OCL|✔|
|[[Heart_Wall|Heart Wall]]|Structured Grid|Medical Imaging|CUDA, OMP, OCL||
|[[MUMmerGPU|MUMmerGPU]]|Graph Traversal|Bioinformatics|CUDA, OMP||
|[[CFD_Solver|CFD Solver]]|Unstructured Grid|Fluid Dynamics|CUDA, OMP, OCL||
|[[LU_Decomposition|LU Decomposition]]|Dense Linear Algebra|Linear Algebra|CUDA, OMP, OCL|✔|
|[[HotSpot|HotSpot]]|Structured Grid|Physics Simulation|CUDA, OMP, OCL||
|[[Back_Propagation|Back Propogation]]|Unstructured Grid|Pattern Recognition|CUDA, OMP, OCL||
|[[Needleman-Wunsch|Needleman-Wunsch]]|Dynamic Programming|Bioinformatics|CUDA, OMP, OCL|✔|
|[[Kmeans|Kmeans]]|Dense Linear Algebra|Data Mining|CUDA, OMP, OCL||
|[[Graph_traversal|Breadth-First Search]]|Graph Traversal|Graph Algorithms|CUDA, OMP, OCL||
|[[SRAD|SRAD]]|Structured Grid|Image Processing|CUDA, OMP, OCL|✔|
|[[Streamcluster|Streamcluster]]|Dense Linear Algebra|Data Mining|CUDA, OMP, OCL||
|[[Particle_Filter|Particle Filter]]|Structured Grid|Medical Imaging|CUDA, OMP, OCL||
|[[PathFinder|PathFinder]]|Dynamic Programming|Grid Traversal|CUDA, OMP, OCL||
|[[Gaussian_Elimination|Gaussian Elimination]]|Dense Linear Algebra|Linear Algebra|CUDA, OCL||
|[[k-Nearest_Neighbors|k-Nearest Neighbors]]|Dense Linear Algebra|Data Mining|CUDA, OMP, OCL||
|[[LavaMD2|LavaMD2]]|N-Body|Molecular Dynamics|CUDA, OMP, OCL||
|[[Myocyte|Myocyte]]|Structured Grid|Biological Simulation|CUDA, OMP, OCL||
|[[B+_Tree|B+ Tree]]|Graph Traversal|Search|CUDA, OMP, OCL||
|[[GPUDWT|GPUDWT]]|Spectral Method|Image/Video Compression|CUDA, OCL||
|[[Hybrid_Sort|Hybrid Sort]]|Sorting|Sorting Algorithms|CUDA, OCL||
|[[Hotspot3D|Hotspot3D]]|Structured Grid|Physics Simulation|CUDA, OCL, OMP|Hotspot for 3D IC|
|[[Huffman|Huffman]]|Finite State Machine|Lossless data compression|CUDA, OCL||

Other applications under evaluation:

^Applications	^Dwarves	^Domains	^Parallel Model	^Comment ^
|[[SQLite Select|SQLite Select]]|Map Reduce|Relational Database|CUDA|This benchmark needs an OCL version and also may be too simple|
|[[3D Stencil|3D Stencil]]|Structured Grid|Cellular Automation|CUDA|Will be superseded by a more sophisticated 3D benchmark|

//1. Ana Lucia Varbanescu and Jianbin Fang, Delft University of Technology contributed the OpenCL version.



//2. In collaboration with Lawrence Livermore National Laboratory.

===== License =====
Please read the [[http://www.cs.virginia.edu/~kw5na/license.htm|Rodinia license]].

Several applications/libraries come with [[http://www.cs.virginia.edu/~kw5na/license_list.htm|their own licenses]].

Also, if your use of Rodinia results in a publication, please cite:

[1] S. Che, M. Boyer, J. Meng, D. Tarjan, J. W. Sheaffer, S.-H. Lee, and K. Skadron. 
Rodinia: A Benchmark Suite for Heterogeneous Computing. In Proceedings of the IEEE 
International Symposium on Workload Characterization (IISWC), pp. 44-54, Oct. 2009.

[2] S. Che, J. W. Sheaffer, M. Boyer, L. G. Szafaryn, L. Wang, and K. Skadron. 
A Characterization of the Rodinia Benchmark Suite with Comparison to Contemporary 
CMP Workloads. In Proceedings of the IEEE International Symposium on Workload 
Characterization, Dec. 2010.

This work is supported by NSF grant nos. IIS-0612049, CNS-0916908 and CNS-0615277, a grant from the SRC under task no. 1607, and grants from AMD, NEC labs, and NVIDIA Research.

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