====== 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 ([[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 [[https://essaylamba.com|EssayLamba]] and 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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