Heterogeneous multiprocessor/multicore/manycore systems are promising alternatives to traditional homogeneous multiprocessor systems and can potentially offer better tradeoffs among energy efficiency, performance, flexibility, scalability, and cost. However exploring their heterogeneities is not well supported by traditional benchmarks which rely on compliers and operating systems developed for homogenous multiprocessor systems. To overcome these issues, this project developed a heterogeneous multiprocessor benchmark suite called COSMIC (Communication-Observant Schedulable Memory-Inclusive Computation).
Project Member: Zhongyuan Tian, Bin Li (Intel), Ravi Iyer (Intel), Ramesh Illikkal (Intel), Jiang Xu, Zhifei Wang, Xuanqi Chen, Jun Feng, Shixi Chen, Jiaxu Zhang, Xiao Li
Maintained by: Zhongyuan Tian (firstname.lastname@example.org). If there is any inquiry or suggestion, please do not hesitate to contact us.
Past Member: Rafael Kioji Vivas Maeda, Zhe Wang, Weichen Liu, Peng Yang, Haoran Li, Xiaowen Wu, Zhehui Wang, Xuan Wang, Yaoyao Ye, Mahdi Nikdast, Luan H.K. Duong
COSMIC is systematically developed from the algorithms of typical multiprocessor applications. Besides implementing the applications in high-level programming languages, COSMIC uses a formal computational model TCG to explicitly capture the computation and communication requirements of multiprocessor applications. It provides a tool to automatically allocate memory and partition and schedule tasks based on user-defined methods.
COSMIC heterogeneous multiprocessor benchmark suite currently includes the following main components and set of applications.
|Cifar-train||Training phase of a Deep Convolutional Neural Network for the Cifar-10 dateset.|
|Facerec-train||Training phase of a Deep Convolutional Neural Network for face recognition.|
|AlexNet-inf||Interfence phase of the DCNN with 5 convolutional layers.|
|Machine Learning - ALIP||Machine learning based image indexing.|
|Machine Learning - FMP||Financial market prediction using machine learning.|
|HPCG||Conjugate gradient algorithm. Generates a linear system of a three-dimensional heat diffusion problem.|
|Pennant||Lagrangian staggered-grid hydrodynamics algorithm on 2-D unstructured finite-volume mesh.|
|Snap||Performance modelling of a modern discrete ordinates neutral particle transport application.|
|Stream||Synthetic benchmark measuring the memory bandwidth and a corresponding computation rate for four simple vector kernels.|
|Molecular Dynamics||Simulating molecular dynamics when molecules are shot to surfaces of solid atoms. Developed with Prof. Wenjing Ye.|
|Ray Tracing||3D scenes rendering. Developed with Prof. Pedro Sander.|
|Ultrasound||Medical diagnostics using 2D/3D ultrasound imaging. Developed with Prof. Weichuan Yu.|
|LDPC||Low-density parity-check code encoder. Developed with Prof. Wai Ho Mow.|
|TURBO||Turbo code decoder. Developed with Prof. Wai Ho Mow.|
|Reed-Solomon||Reed-Solomon code encoder and decoder.|
|FFT||Fast Fourier Transform with complex number inputs.|
Or you can download the full package directly.
COSMIC is made openly available under the following license. Please cite the following paper if it is used.
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