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ORCIDMichael G. Gowanlock
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- affiliation: Northern Arizona University, School of Informatics, Computing & Cyber Systems, Flagstaff, USA
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2020 – today
- 2023
[j14]Daniel Kramer
, Michael Gowanlock, D. E. Trilling, A. McNeill, N. Erasmus:
Removing aliases in time-series photometry. Astron. Comput. 44: 100711 (2023)- [c23]Michael Gowanlock, Benoît Gallet, Brian Donnelly:
Optimization and Comparison of Coordinate- and Metric-Based Indexes on GPUs for Distance Similarity Searches. ICCS (2) 2023: 357-364 - [c22]Kaitlyn Lee, Brian Donnelly, Tomer Sery, Dan Ilan, Bertrand Cambou, Michael Gowanlock:
Evaluating Accelerators for a High-Throughput Hash-Based Security Protocol. ICPP Workshops 2023: 40-49 - 2022
- [j13]Michael G. Gowanlock, N. R. Butler, D. E. Trilling, A. McNeill:
GPU-enabled searches for periodic signals of unknown shape. Astron. Comput. 38: 100511 (2022) - [c21]Benoît Gallet, Michael Gowanlock:
Leveraging GPU Tensor Cores for Double Precision Euclidean Distance Calculations. HIPC 2022: 135-144 - [i7]Benoît Gallet, Michael Gowanlock:
Computing Double Precision Euclidean Distances using GPU Tensor Cores. CoRR abs/2209.11287 (2022) - 2021
- [j12]Michael G. Gowanlock, Daniel Kramer, D. E. Trilling, N. R. Butler, Brian Donnelly:
Fast period searches using the Lomb-Scargle algorithm on Graphics Processing Units for large datasets and real-time applications. Astron. Comput. 36: 100472 (2021) - [j11]Benoît Gallet, Michael Gowanlock:
Heterogeneous CPU-GPU Epsilon Grid Joins: Static and Dynamic Work Partitioning Strategies. Data Sci. Eng. 6(1): 39-62 (2021) - [j10]Michael Gowanlock:
Hybrid KNN-join: Parallel nearest neighbor searches exploiting CPU and GPU architectural features. J. Parallel Distributed Comput. 149: 119-137 (2021) - [c20]Jordan Wright, Zane Fink, Michael Gowanlock, Christopher Robert Philabaum, Brian Donnelly, Bertrand Cambou:
A Symmetric Cipher Response-Based Cryptography Engine Accelerated Using GPGPU. CNS 2021: 146-154 - [c19]Madhav Poudel, Michael Gowanlock:
CUDA-DClust+: Revisiting Early GPU-Accelerated DBSCAN Clustering Designs. HiPC 2021: 354-363 - [c18]Colin Taylor, Michael Gowanlock:
Accelerating the Yinyang K-Means Algorithm Using the GPU. ICDE 2021: 1835-1840 - [c17]Michael Gowanlock, Benoît Gallet:
Data-Intensive Computing Modules for Teaching Parallel and Distributed Computing. IPDPS Workshops 2021: 350-357 - [c16]Kaitlyn Lee, Michael Gowanlock, Bertrand Cambou:
SABER-GPU: A Response-Based Cryptography Algorithm for SABER on the GPU. PRDC 2021: 123-132 - [c15]Michael Gowanlock, Zane Fink, Ben Karsin, Jordan Wright:
A study of work distribution and contention in database primitives on heterogeneous CPU/GPU architectures. SAC 2021: 311-320 - [c14]Christopher Robert Philabaum, Christopher Coffey, Bertrand Cambou, Michael Gowanlock:
A Response-Based Cryptography Engine in Distributed-Memory. SAI (3) 2021: 904-922 - 2020
- [j9]Bertrand Cambou, Michael Gowanlock, Julie Heynssens, Saloni Jain, Christopher Robert Philabaum, Duane Booher, Ian Burke, Jack Garrard, Donald Telesca, Laurent Njilla:
Securing Additive Manufacturing with Blockchains and Distributed Physically Unclonable Functions. Cryptogr. 4(2): 17 (2020) - [c13]Benoît Gallet, Michael Gowanlock:
HEGJoin: Heterogeneous CPU-GPU Epsilon Grids for Accelerated Distance Similarity Join. DASFAA (3) 2020: 372-388 - [c12]Brian Donnelly, Michael Gowanlock:
A coordinate-oblivious index for high-dimensional distance similarity searches on the GPU. ICS 2020: 8:1-8:12
2010 – 2019
- 2019
- [j8]Michael Gowanlock, Ben Karsin:
Accelerating the similarity self-join using the GPU. J. Parallel Distributed Comput. 133: 107-123 (2019) - [j7]Michael Gowanlock, Ben Karsin:
A hybrid CPU/GPU approach for optimizing sorting throughput. Parallel Comput. 85: 45-55 (2019) - [j6]Michael Gowanlock, Cody M. Rude, David M. Blair, Justin D. Li, Victor Pankratius:
A Hybrid Approach for Optimizing Parallel Clustering Throughput using the GPU. IEEE Trans. Parallel Distributed Syst. 30(4): 766-777 (2019) - [c11]Michael Gowanlock:
KNN-Joins Using a Hybrid Approach: Exploiting CPU/GPU Workload Characteristics. GPGPU@ASPLOS 2019: 33-42 - [c10]Michael Gowanlock, Ben Karsin:
GPU-Accelerated Similarity Self-Join for Multi-Dimensional Data. DaMoN 2019: 6:1-6:9 - [c9]Michael Gowanlock, Ben Karsin, Zane Fink, Jordan Wright:
Accelerating the Unacceleratable: Hybrid CPU/GPU Algorithms for Memory-Bound Database Primitives. DaMoN 2019: 7:1-7:11 - [c8]Michael Gowanlock:
Hybrid CPU/GPU clustering in shared memory on the billion point scale. ICS 2019: 35-45 - [c7]Benoît Gallet, Michael Gowanlock:
Load Imbalance Mitigation Optimizations for GPU-Accelerated Similarity Joins. IPDPS Workshops 2019: 396-405 - 2018
- [j5]Michael G. Gowanlock, Justin D. Li, Cody M. Rude, Victor Pankratius:
Parallel optimization of signal detection in active magnetospheric signal injection experiments. Comput. Geosci. 114: 107-116 (2018) - [c6]Michael Gowanlock, Ben Karsin:
GPU Accelerated Self-Join for the Distance Similarity Metric. IPDPS Workshops 2018: 477-486 - [c5]Michael Gowanlock, Ben Karsin:
Sorting Large Datasets with Heterogeneous CPU/GPU Architectures. IPDPS Workshops 2018: 560-569 - [i6]Michael Gowanlock, Ben Karsin:
GPU Accelerated Self-join for the Distance Similarity Metric. CoRR abs/1803.04120 (2018) - [i5]Michael Gowanlock, Ben Karsin:
GPU Accelerated Similarity Self-Join for Multi-Dimensional Data. CoRR abs/1809.09930 (2018) - [i4]Michael Gowanlock:
Technical Report: KNN Joins Using a Hybrid Approach: Exploiting CPU/GPU Workload Characteristics. CoRR abs/1810.04758 (2018) - 2017
- [j4]Michael G. Gowanlock, David M. Blair, Victor Pankratius:
Optimizing Parallel Clustering Throughput in Shared Memory. IEEE Trans. Parallel Distributed Syst. 28(9): 2595-2607 (2017) - [c4]Michael G. Gowanlock, Cody M. Rude, David M. Blair, Justin D. Li, Victor Pankratius:
Clustering Throughput Optimization on the GPU. IPDPS 2017: 832-841 - 2016
- [j3]Victor Pankratius, Justin D. Li, Michael G. Gowanlock, David M. Blair, Cody Rude, Tom Herring, Frank D. Lind, Philip J. Erickson, Colin J. Lonsdale:
Computer-Aided Discovery: Toward Scientific Insight Generation with Machine Support. IEEE Intell. Syst. 31(4): 3-10 (2016) - [j2]Michael G. Gowanlock, Henri Casanova:
Distance Threshold Similarity Searches: Efficient Trajectory Indexing on the GPU. IEEE Trans. Parallel Distributed Syst. 27(9): 2533-2545 (2016) - [c3]Michael G. Gowanlock, David M. Blair, Victor Pankratius:
Exploiting Variant-Based Parallelism for Data Mining of Space Weather Phenomena. IPDPS 2016: 760-769 - 2015
- [c2]Michael G. Gowanlock, Henri Casanova:
Indexing of Spatiotemporal Trajectories for Efficient Distance Threshold Similarity Searches on the GPU. IPDPS 2015: 387-396 - 2014
- [c1]Michael G. Gowanlock, Henri Casanova:
Distance threshold similarity searches on spatiotemporal trajectories using GPGPU. HiPC 2014: 1-10 - [i3]Michael G. Gowanlock, Henri Casanova:
Technical Report: Parallel Distance Threshold Query Processing for Spatiotemporal Trajectory Databases on the GPU. CoRR abs/1405.7461 (2014) - [i2]Michael G. Gowanlock, Henri Casanova:
Technical Report: Towards Efficient Indexing of Spatiotemporal Trajectories on the GPU for Distance Threshold Similarity Searches. CoRR abs/1410.2698 (2014) - 2013
- [j1]Michael G. Gowanlock, Rich Gazan:
Assessing researcher interdisciplinarity: a case study of the University of Hawaii NASA Astrobiology Institute. Scientometrics 94(1): 133-161 (2013) - 2012
- [i1]Michael G. Gowanlock, Rich Gazan:
Assessing Researcher Interdisciplinarity: A Case Study of the University of Hawaii NASA Astrobiology Institute. CoRR abs/1204.5563 (2012)
Coauthor Index
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