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 | 2012 | |
|---|---|---|
| j1 |      | Vignesh T. Ravi, Wenjing Ma, David Chiu, Gagan Agrawal: Compiler and runtime support for enabling reduction computations on heterogeneous systems. Concurrency and Computation: Practice and Experience 24(5): 463-480 (2012) |
| c17 | | Vignesh T. Ravi, Michela Becchi, Wei Jiang, Gagan Agrawal, Srimat T. Chakradhar: Scheduling Concurrent Applications on a Cluster of CPU-GPU Nodes. CCGRID 2012: 140-147 |
| c16 | | Mai Zheng, Vignesh T. Ravi, Wenjing Ma, Feng Qin, Gagan Agrawal: GMProf: A low-overhead, fine-grained profiling approach for GPU programs. HiPC 2012: 1-10 |
| c15 | | Michela Becchi, Kittisak Sajjapongse, Ian Graves, Adam M. Procter, Vignesh T. Ravi, Srimat T. Chakradhar: A virtual memory based runtime to support multi-tenancy in clusters with GPUs. HPDC 2012: 97-108 |
| c14 | | Vignesh T. Ravi, Michela Becchi, Gagan Agrawal, Srimat T. Chakradhar: ValuePack: value-based scheduling framework for CPU-GPU clusters. SC 2012: 53 |
| 2011 | ||
| c13 | | Xin Huo, Vignesh T. Ravi, Gagan Agrawal: Porting irregular reductions on heterogeneous CPU-GPU configurations. HiPC 2011: 1-10 |
| c12 | | Vignesh T. Ravi, Gagan Agrawal: A dynamic scheduling framework for emerging heterogeneous systems. HiPC 2011: 1-10 |
| c11 | | Vignesh T. Ravi, Michela Becchi, Gagan Agrawal, Srimat T. Chakradhar: Supporting GPU sharing in cloud environments with a transparent runtime consolidation framework. HPDC 2011: 217-228 |
| c10 | | Xin Huo, Vignesh T. Ravi, Wenjing Ma, Gagan Agrawal: An execution strategy and optimized runtime support for parallelizing irregular reductions on modern GPUs. ICS 2011: 2-11 |
| c9 | | Mai Zheng, Vignesh T. Ravi, Feng Qin, Gagan Agrawal: GRace: a low-overhead mechanism for detecting data races in GPU programs. PPOPP 2011: 135-146 |
| 2010 | ||
| c8 | | Wei Jiang, Vignesh T. Ravi, Gagan Agrawal: A Map-Reduce System with an Alternate API for Multi-core Environments. CCGRID 2010: 84-93 |
| c7 | | Xin Huo, Vignesh T. Ravi, Wenjing Ma, Gagan Agrawal: Approaches for parallelizing reductions on modern GPUs. HiPC 2010: 1-10 |
| c6 | | Venkatram Ramanathan, Wenjing Ma, Vignesh T. Ravi, Tantan Liu, Gagan Agrawal: Parallelizing an Information Theoretic Co-clustering Algorithm Using a Cloud Middleware. ICDM Workshops 2010: 186-193 |
| c5 | | Vignesh T. Ravi, Wenjing Ma, David Chiu, Gagan Agrawal: Compiler and runtime support for enabling generalized reduction computations on heterogeneous parallel configurations. ICS 2010: 137-146 |
| 2009 | ||
| c4 | | Vignesh T. Ravi, Gagan Agrawal: Performance Issues in Parallelizing Data-Intensive Applications on a Multi-core Cluster. CCGRID 2009: 308-315 |
| c3 | | Wei Jiang, Vignesh T. Ravi, Gagan Agrawal: Comparing map-reduce and FREERIDE for data-intensive applications. CLUSTER 2009: 1-10 |
| c2 | | Vignesh T. Ravi, Gagan Agrawal: Integrating and optimizing transactional memory in a data mining middleware. HiPC 2009: 215-224 |
| c1 | | Leonid Glimcher, Vignesh T. Ravi, Gagan Agrawal: Supporting load balancing for distributed data-intensive applications. HiPC 2009: 235-244 |
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