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2020 – today
- 2022
[c209]Atharva Gondhalekar, Thomas Twomey, Wu-chun Feng:
On the Characterization of the Performance-Productivity Gap for FPGA. HPEC 2022: 1-8- [c208]Paul Sathre, Atharva Gondhalekar, Wu-chun Feng:
Edge-Connected Jaccard Similarity for Graph Link Prediction on FPGA. HPEC 2022: 1-10 - [c207]Karim Youssef, Abdullah Al Raqibul Islam, Keita Iwabuchi, Wu-chun Feng, Roger Pearce:
Optimizing Performance and Storage of Memory-Mapped Persistent Data Structures. HPEC 2022: 1-7 - [c206]Karim Youssef, Niteya Shah, Maya B. Gokhale, Roger Pearce, Wu-chun Feng:
AutoPager: Auto-tuning Memory-Mapped I/O Parameters in Userspace. HPEC 2022: 1-7 - [c205]Frank Wanye
, Vitaliy Gleyzer, Edward K. Kao, Wu-chun Feng:
On the Parallelization of MCMC for Community Detection. ICPP 2022: 87:1-87:13 - [i6]Saikat Dey, Sonal Jha, Wu-chun Feng:
G2A2: An Automated Graph Generator with Attributes and Anomalies. CoRR abs/2210.07449 (2022) - 2021
- [j49]Xuewen Cui, Wu-chun Feng:
IterML: Iterative Machine Learning for Intelligent Parameter Pruning and Tuning in Graphics Processing Units. J. Signal Process. Syst. 93(4): 391-403 (2021) - [c204]Karim Youssef, Keita Iwabuchi, Wu-Chun Feng, Roger Pearce:
Privateer: Multi-versioned Memory-mapped Data Stores for High-Performance Data Science. HPEC 2021: 1-7 - [c203]Sajal Dash, Qais Al-Hajri, Wu-chun Feng, Harold R. Garner, Ramu Anandakrishnan:
Scaling Out a Combinatorial Algorithm for Discovering Carcinogenic Gene Combinations to Thousands of GPUs. IPDPS 2021: 837-846 - [c202]Sajal Dash, Junqi Yin, Mallikarjun Shankar, Feiyi Wang, Wu-chun Feng:
Mitigating Catastrophic Forgetting in Deep Learning in a Streaming Setting Using Historical Summary. DRBSD@SC 2021: 11-18 - [i5]Frank Wanye, Vitaliy Gleyzer, Edward K. Kao, Wu-chun Feng:
Topology-Guided Sampling for Fast and Accurate Community Detection. CoRR abs/2108.06651 (2021) - [i4]Garvit Goel, Jingyuan Qi, Wu-chun Feng, Guohua Cao:
A Deep-Learning Framework for Improving COVID-19 CT Image Quality and Diagnostic Accuracy. CoRR abs/2112.09216 (2021) - 2020
- [j48]Moeti Masiane, Anne Driscoll, Wu-chun Feng, John E. Wenskovitch, Chris North:
Towards insight-driven sampling for big data visualisation. Behav. Inf. Technol. 39(7): 788-807 (2020) - [c201]Vignesh Adhinarayanan, Wu-chun Feng:
Approximate Pattern Matching for On-Chip Interconnect Traffic Prediction. PACT 2020: 357-358 - [c200]Sarunya Pumma, Daniele Buono, Fabio Checconi, Xinyu Que, Wu-chun Feng:
Alleviating Load Imbalance in Data Processing for Large-Scale Deep Learning. CCGRID 2020: 262-271 - [c199]Karim Youssef, Wu-chun Feng:
SparkLeBLAST: Scalable Parallelization of BLAST Sequence Alignment Using Spark. CCGRID 2020: 539-548 - [c198]Atharva Gondhalekar, Wu-Chun Feng:
Exploring FPGA Optimizations in OpenCL for Breadth-First Search on Sparse Graph Datasets. FPL 2020: 133-137 - [c197]Wu-chun Feng, Da Zhang, Jing Zhang, Kaixi Hou, Sarunya Pumma, Hao Wang:
A Feasibility Study for MPI over HDFS. HPEC 2020: 1-7 - [c196]Paul Sathre, Atharva Gondhalekar, Mohamed W. Hassan, Wu-Chun Feng:
MetaCL: Automated "Meta" OpenCL Code Generation for High-Level Synthesis on FPGA. HPEC 2020: 1-8 - [c195]Gregory D. Abram, Vignesh Adhinarayanan, Wu-chun Feng, David H. Rogers, James P. Ahrens:
ETH: An Architecture for Exploring the Design Space of In-situ Scientific Visualization. IPDPS 2020: 515-526
2010 – 2019
- 2019
- [j47]Sarunya Pumma, Min Si, Wu-Chun Feng, Pavan Balaji:
Scalable Deep Learning via I/O Analysis and Optimization. ACM Trans. Parallel Comput. 6(2): 6:1-6:34 (2019) - [j46]Xiaodong Yu, Hao Wang, Wu-chun Feng, Hao Gong, Guohua Cao:
GPU-Based Iterative Medical CT Image Reconstructions. J. Signal Process. Syst. 91(3-4): 321-338 (2019) - [c194]Ahmed E. Helal, Ashwin M. Aji, Michael L. Chu, Bradford M. Beckmann, Wu-chun Feng:
Adaptive Task Aggregation for High-Performance Sparse Solvers on GPUs. PACT 2019: 324-336 - [c193]Xuewen Cui, Wu-chun Feng:
Iterative machine learning (IterML) for effective parameter pruning and tuning in accelerators. CF 2019: 16-23 - [c192]Paul Sathre, Mark K. Gardner, Wu-chun Feng:
On the Portability of CPU-Accelerated Applications via Automated Source-to-Source Translation. HPC Asia 2019: 1-8 - [c191]Mohamed W. Hassan, Scott Pakin, Wu-chun Feng:
C to D-Wave: A High-level C Compilation Framework for Quantum Annealers. HPEC 2019: 1-8 - [c190]Frank Wanye, Vitaliy Gleyzer, Wu-chun Feng:
Fast Stochastic Block Partitioning via Sampling. HPEC 2019: 1-7 - 2018
- [j45]Kaixi Hou, Hao Wang, Wu-Chun Feng:
A Framework for the Automatic Vectorization of Parallel Sort on x86-Based Processors. IEEE Trans. Parallel Distributed Syst. 29(5): 958-972 (2018) - [c189]Jing Zhang, Ashwin M. Aji, Michael L. Chu, Hao Wang, Wu-chun Feng:
Taming irregular applications via advanced dynamic parallelism on GPUs. CF 2018: 146-154 - [c188]Bishwajit Dutta, Vignesh Adhinarayanan, Wu-chun Feng:
GPU power prediction via ensemble machine learning for DVFS space exploration. CF 2018: 240-243 - [c187]Ahmed E. Helal, Changhee Jung, Wu-chun Feng, Yasser Y. Hanafy:
CommAnalyzer: automated estimation of communication cost and scalability on HPC clusters from sequential code. HPDC 2018: 80-91 - [c186]Konstantinos Krommydas, Paul Sathre, Ruchira Sasanka, Wu-chun Feng:
A Framework for Auto-Parallelization and Code Generation: An Integrative Case Study with Legacy FORTRAN Codes. ICPP 2018: 57:1-57:10 - [c185]Kaixi Hou, Hao Wang, Wu-chun Feng, Jeffrey S. Vetter, Seyong Lee:
Highly Efficient Compensation-Based Parallelism for Wavefront Loops on GPUs. IPDPS 2018: 276-285 - [c184]Vignesh Adhinarayanan, Bishwajit Dutta, Wu-chun Feng:
Making a Case for Green High-Performance Visualization Via Embedded Graphics Processors. IPDPS Workshops 2018: 721-724 - [c183]Mohamed W. Hassan, Ahmed E. Helal, Peter M. Athanas, Wu-Chun Feng, Yasser Y. Hanafy:
Exploring FPGA-specific Optimizations for Irregular OpenCL Applications. ReConFig 2018: 1-8 - [c182]Paul Sathre, Ahmed E. Helal, Wu-chun Feng:
A Composable Workflow for Productive Heterogeneous Computing on FPGAs via Whole-Program Analysis and Transformation. ReConFig 2018: 1-8 - 2017
- [j44]Sarunya Pumma, Wu-chun Feng, Phond Phunchongharn, Sylvain Chapeland, Tiranee Achalakul:
A runtime estimation framework for ALICE. Future Gener. Comput. Syst. 72: 65-77 (2017) - [j43]Annette C. Feng, Mark K. Gardner, Wu-chun Feng:
Parallel programming with pictures is a Snap! J. Parallel Distributed Comput. 105: 150-162 (2017) - [j42]Jing Zhang, Hao Wang, Wu-chun Feng:
cuBLASTP: Fine-Grained Parallelization of Protein Sequence Search on CPU+GPU. IEEE ACM Trans. Comput. Biol. Bioinform. 14(4): 830-843 (2017) - [c181]Xiaodong Yu, Kaixi Hou, Hao Wang, Wu-chun Feng:
Robotomata: A framework for approximate pattern matching of big data on an automata processor. IEEE BigData 2017: 283-292 - [c180]Xiaodong Yu, Hao Wang, Wu-chun Feng, Hao Gong, Guohua Cao:
An Enhanced Image Reconstruction Tool for Computed Tomography on CPUs. Conf. Computing Frontiers 2017: 97-106 - [c179]Kaixi Hou, Hao Wang, Wu-chun Feng:
GPU-UniCache: Automatic Code Generation of Spatial Blocking for Stencils on CPUs. Conf. Computing Frontiers 2017: 107-116 - [c178]Anshuman Verma, Huiyang Zhou, Skip Booth, Robbie King, James Coole, Andy Keep, John Marshall, Wu-chun Feng:
Developing Dynamic Profiling and Debugging Support in OpenCL for FPGAs. DAC 2017: 56:1-56:6 - [c177]Sajal Dash, Anshuman Verma, Chris North, Wu-chun Feng:
Portable Parallel Design of Weighted Multi-Dimensional Scaling for Real-Time Data Analysis. HPCC/SmartCity/DSS 2017: 10-17 - [c176]Sarunya Pumma, Min Si, Wu-chun Feng, Pavan Balaji:
Towards Scalable Deep Learning via I/O Analysis and Optimization. HPCC/SmartCity/DSS 2017: 223-230 - [c175]Sarunya Pumma, Min Si, Wu-chun Feng, Pavan Balaji:
Parallel I/O Optimizations for Scalable Deep Learning. ICPADS 2017: 720-729 - [c174]Marziyeh Nourian, Xiang Wang, Xiaodong Yu, Wu-chun Feng, Michela Becchi:
Demystifying automata processing: GPUs, FPGAs or Micron's AP? ICS 2017: 1:1-1:11 - [c173]Kaixi Hou, Weifeng Liu, Hao Wang, Wu-chun Feng:
Fast segmented sort on GPUs. ICS 2017: 12:1-12:10 - [c172]Ahmed E. Helal, Wu-chun Feng, Changhee Jung, Yasser Y. Hanafy:
AutoMatch: An automated framework for relative performance estimation and workload distribution on heterogeneous HPC systems. IISWC 2017: 32-42 - [c171]Xiaodong Yu, Kaixi Hou, Hao Wang, Wu-chun Feng:
A framework for fast and fair evaluation of automata processing hardware. IISWC 2017: 120-121 - [c170]Jing Zhang, Sanchit Misra, Hao Wang, Wu-chun Feng:
Eliminating Irregularities of Protein Sequence Search on Multicore Architectures. IPDPS 2017: 62-71 - [c169]Xuewen Cui, Thomas R. W. Scogland, Bronis R. de Supinski, Wu-chun Feng:
Directive-Based Partitioning and Pipelining for Graphics Processing Units. IPDPS 2017: 575-584 - [c168]Hao Wang, Jing Zhang, Da Zhang, Sarunya Pumma, Wu-chun Feng:
PaPar: A Parallel Data Partitioning Framework for Big Data Applications. IPDPS 2017: 605-614 - [c167]Kaixi Hou, Wu-chun Feng, Shuai Che:
Auto-Tuning Strategies for Parallelizing Sparse Matrix-Vector (SpMV) Multiplication on Multi- and Many-Core Processors. IPDPS Workshops 2017: 713-722 - [c166]Vignesh Adhinarayanan, Wu-chun Feng, David H. Rogers, James P. Ahrens, Scott Pakin:
Characterizing and Modeling Power and Energy for Extreme-Scale In-Situ Visualization. IPDPS 2017: 978-987 - 2016
- [j41]Jing Zhang, Sanchit Misra, Hao Wang, Wu-chun Feng:
muBLASTP: database-indexed protein sequence search on multicore CPUs. BMC Bioinform. 17: 443:1-443:14 (2016) - [j40]Ashwin M. Aji, Antonio J. Peña, Pavan Balaji, Wu-chun Feng:
MultiCL: Enabling automatic scheduling for task-parallel workloads in OpenCL. Parallel Comput. 58: 37-55 (2016) - [j39]Xiaokui Shu, Jing Zhang, Danfeng (Daphne) Yao, Wu-chun Feng:
Fast Detection of Transformed Data Leaks. IEEE Trans. Inf. Forensics Secur. 11(3): 528-542 (2016) - [j38]Ashwin M. Aji, Lokendra S. Panwar, Feng Ji, Karthik Murthy, Milind Chabbi, Pavan Balaji, Keith R. Bisset, James Dinan, Wu-chun Feng, John M. Mellor-Crummey, Xiaosong Ma, Rajeev Thakur:
MPI-ACC: Accelerator-Aware MPI for Scientific Applications. IEEE Trans. Parallel Distributed Syst. 27(5): 1401-1414 (2016) - [j37]Konstantinos Krommydas, Wu-chun Feng, Christos D. Antonopoulos, Nikolaos Bellas:
OpenDwarfs: Characterization of Dwarf-Based Benchmarks on Fixed and Reconfigurable Architectures. J. Signal Process. Syst. 85(3): 373-392 (2016) - [c165]Xiaodong Yu, Wu-chun Feng, Danfeng (Daphne) Yao, Michela Becchi:
O3FA: A Scalable Finite Automata-based Pattern-Matching Engine for Out-of-Order Deep Packet Inspection. ANCS 2016: 1-11 - [c164]Konstantinos Krommydas, Ruchira Sasanka, Wu-chun Feng:
Bridging the FPGA programmability-portability Gap via automatic OpenCL code generation and tuning. ASAP 2016: 213-218 - [c163]Ramu Anandakrishnan, Mayank Daga, Alexey Onufriev, Wu-chun Feng:
Multiscale Approximation with Graphical Processing Units for Multiplicative Speedup in Molecular Dynamics. BCB 2016: 453-462 - [c162]Xiaodong Yu, Hao Wang, Wu-chun Feng, Hao Gong, Guohua Cao:
cuART: Fine-Grained Algebraic Reconstruction Technique for Computed Tomography Images on GPUs. CCGrid 2016: 165-168 - [c161]Vignesh Adhinarayanan, Balaji Subramaniam, Wu-chun Feng:
Online Power Estimation of Graphics Processing Units. CCGrid 2016: 245-254 - [c160]Xuewen Cui, Thomas R. W. Scogland, Bronis R. de Supinski, Wu-Chun Feng:
Directive-Based Pipelining Extension for OpenMP. CLUSTER 2016: 481-484 - [c159]Konstantinos Krommydas, Ahmed E. Helal, Anshuman Verma, Wu-chun Feng:
Bridging the Performance-Programmability Gap for FPGAs via OpenCL: A Case Study with OpenDwarfs. FCCM 2016: 198 - [c158]Konstantinos Krommydas, Wu-Chun Feng:
Telescoping Architectures: Evaluating Next-Generation Heterogeneous Computing. HiPC 2016: 162-171 - [c157]Hao Wang, Weifeng Liu, Kaixi Hou, Wu-chun Feng:
Parallel Transposition of Sparse Data Structures. ICS 2016: 33:1-33:13 - [c156]Vignesh Adhinarayanan, Indrani Paul, Joseph L. Greathouse, Wei Huang, Ashutosh Pattnaik, Wu-chun Feng:
Measuring and modeling on-chip interconnect power on real hardware. IISWC 2016: 23-33 - [c155]Kaixi Hou, Hao Wang, Wu-chun Feng:
AAlign: A SIMD Framework for Pairwise Sequence Alignment on x86-Based Multi-and Many-Core Processors. IPDPS 2016: 780-789 - [c154]Annette C. Feng, Wu-chun Feng:
Parallel Programming with Pictures in a Snap! IPDPS Workshops 2016: 950-957 - [c153]Chung-Hsing Hsu, Wu-chun Feng:
The Right Metric for Efficient Supercomputing: A Ten-Year Retrospective. IPDPS Workshops 2016: 1090-1093 - [c152]Vignesh Adhinarayanan, Wu-chun Feng:
An automated framework for characterizing and subsetting GPGPU workloads. ISPASS 2016: 307-317 - [c151]Islam Harb, Wu-Chun Feng:
Characterizing Performance and Power towards Efficient Synchronization of GPU Kernels. MASCOTS 2016: 451-456 - [c150]Ahmed E. Helal, Paul Sathre, Wu-chun Feng:
MetaMorph: a library framework for interoperable kernels on multi- and many-core clusters. SC 2016: 119-129 - 2015
- [j36]Juan Antonio Gómez Pulido, Bertil Schmidt, Wu-chun Feng:
Accelerating Bioinformatics Applications via Emerging Parallel Computing Systems. IEEE ACM Trans. Comput. Biol. Bioinform. 12(5): 971-972 (2015) - [j35]Thomas R. W. Scogland, Wu-chun Feng, Barry Rountree, Bronis R. de Supinski:
CoreTSAR: Core Task-Size Adapting Runtime. IEEE Trans. Parallel Distributed Syst. 26(11): 2970-2983 (2015) - [c149]Ashwin Mandayam Aji, Antonio J. Peña, Pavan Balaji, Wu-chun Feng:
Automatic Command Queue Scheduling for Task-Parallel Workloads in OpenCL. CLUSTER 2015: 42-51 - [c148]Xiaokui Shu, Jing Zhang, Danfeng Yao, Wu-chun Feng:
Rapid Screening of Transformed Data Leaks with Efficient Algorithms and Parallel Computing. CODASPY 2015: 147-149 - [c147]Da Zhang, Hao Wang, Kaixi Hou, Jing Zhang, Wu-chun Feng:
pDindel: Accelerating indel detection on a multicore CPU architecture with SIMD. ICCABS 2015: 1-6 - [c146]Konstantinos Krommydas, Ruchira Sasanka, Wu-chun Feng:
GLAF: A Visual Programming and Auto-tuning Framework for Parallel Computing. ICPP 2015: 859-868 - [c145]Kaixi Hou, Hao Wang, Wu-chun Feng:
ASPaS: A Framework for Automatic SIMDization of Parallel Sorting on x86-based Many-core Processors. ICS 2015: 383-392 - [c144]Xiaokui Shu, Jing Zhang, Danfeng Yao, Wu-chun Feng:
Rapid and parallel content screening for detecting transformed data exposure. INFOCOM Workshops 2015: 191-196 - [c143]Wu-chun Feng, Barry Rountree:
HPPAC Introduction and Committees. IPDPS Workshops 2015: 848 - [c142]Rubasri Kalidas, Mayank Daga, Konstantinos Krommydas, Wu-chun Feng:
On the Performance, Energy, and Power of Data-Access Methods in Heterogeneous Computing Systems. IPDPS Workshops 2015: 871-879 - [c141]Vignesh Adhinarayanan, Wu-chun Feng, Jonathan Woodring, David H. Rogers, James P. Ahrens:
On the Greenness of In-Situ and Post-Processing Visualization Pipelines. IPDPS Workshops 2015: 880-887 - [c140]Thomas R. W. Scogland, Wu-chun Feng:
Design and Evaluation of Scalable Concurrent Queues for Many-Core Architectures. ICPE 2015: 63-74 - [i3]Balaji Subramaniam, Wu-chun Feng:
Towards Energy-Proportional Computing Using Subsystem-Level Power Management. CoRR abs/1501.02724 (2015) - [i2]Balaji Subramaniam, Wu-chun Feng:
On the Energy Proportionality of Scale-Out Workloads. CoRR abs/1501.02729 (2015) - 2014
- [j34]Jiangling Yin, Junyao Zhang, Jun Wang, Wu-chun Feng:
SDAFT: A novel scalable data access framework for parallel BLAST. Parallel Comput. 40(10): 697-709 (2014) - [c139]Thomas R. W. Scogland, Wu-Chun Feng:
Locality-aware memory association for multi-target worksharing in OpenMP. PACT 2014: 515-516 - [c138]Konstantinos Krommydas, Wu-chun Feng, Muhsen Owaida, Christos D. Antonopoulos, Nikolaos Bellas:
On the characterization of OpenCL dwarfs on fixed and reconfigurable platforms. ASAP 2014: 153-160 - [c137]Balaji Subramaniam, Wu-chun Feng:
Enabling Efficient Power Provisioning for Enterprise Applications. CCGRID 2014: 71-80 - [c136]Thomas R. W. Scogland, Wu-chun Feng:
Runtime Adaptation for Autonomic Heterogeneous Computing. CCGRID 2014: 562-565 - [c135]Carlo C. del Mundo, Wu-chun Feng:
Towards a performance-portable FFT library for heterogeneous computing. Conf. Computing Frontiers 2014: 11:1-11:10 - [c134]Jiangling Yin, Jun Wang, Wu-chun Feng, Xuhong Zhang, Junyao Zhang:
SLAM: scalable locality-aware middleware for I/O in scientific analysis and visualization. HPDC 2014: 257-260 - [c133]Nataliya Timoshevskaya, Wu-chun Feng:
SAIS-OPT: On the characterization and optimization of the SA-IS algorithm for suffix array construction. ICCABS 2014: 1-6 - [c132]Kaixi Hou, Hao Wang, Wu-chun Feng:
Delivering Parallel Programmability to the Masses via the Intel MIC Ecosystem: A Case Study. ICPP Workshops 2014: 273-282 - [c131]Jing Zhang, Hao Wang, Heshan Lin, Wu-chun Feng:
cuBLASTP: Fine-Grained Parallelization of Protein Sequence Search on a GPU. IPDPS 2014: 251-260 - [c130]James E. McClure, Hao Wang, Jan F. Prins, Cass T. Miller, Wu-chun Feng:
Petascale Application of a Coupled CPU-GPU Algorithm for Simulation and Analysis of Multiphase Flow Solutions in Porous Medium Systems. IPDPS 2014: 583-592 - [c129]Vignesh Adhinarayanan, Thaddeus Koehn, Krzysztof Kepa, Wu-chun Feng, Peter Athanas:
On the performance and energy efficiency of FPGAs and GPUs for polyphase channelization. ReConFig 2014: 1-7 - [c128]Balaji Subramaniam, Wu-chun Feng:
On the Energy Proportionality of Distributed NoSQL Data Stores. PMBS@SC 2014: 264-274 - [c127]Thomas R. W. Scogland, Wu-chun Feng, Barry Rountree, Bronis R. de Supinski:
CoreTSAR: Adaptive Worksharing for Heterogeneous Systems. ISC 2014: 172-186 - [c126]Nabeel Mohamed, Nabanita Maji, Jing Zhang, Nataliya Timoshevskaya, Wu-chun Feng:
Aeromancer: A Workflow Manager for Large-Scale MapReduce-Based Scientific Workflows. TrustCom 2014: 739-746 - [c125]Thomas R. W. Scogland, Craig P. Steffen, Torsten Wilde, Florent Parent, Susan Coghlan, Natalie J. Bates, Wu-chun Feng, Erich Strohmaier:
A power-measurement methodology for large-scale, high-performance computing. ICPE 2014: 149-159 - 2013
- [j33]Eugene Kolker, Vural Özdemir, Lennart Martens, William Hancock, Gordon A. Anderson, Nathaniel Anderson, Sukru Aynacioglu, Ancha V. Baranova, Shawn R. Campagna, Rui Chen, John Choiniere, Stephen P. Dearth, Wu-Chun Feng, Lynnette Ferguson, Geoffrey C. Fox, Dmitrij Frishman, Robert Grossman, Allison P. Heath, Roger Higdon, Mara H. Hutz, Imre Janko, Lihua Jiang, Sanjay Joshi, Alexander E. Kel, Joseph W. Kemnitz, Isaac S. Kohane, Natali Kolker, Doron Lancet, Elaine Lee, Weizhong Li, Andrey Lisitsa, Adrian Llerena, Courtney MacNealy-Koch, Jean-Claude Marshall, Paola Masuzzo, Amanda May, George Mias, Matthew E. Monroe, Elizabeth Montague, Sean Mooney, Alexey I. Nesvizhskii, Santosh Noronha, Gilbert S. Omenn, Harsha Rajasimha, Preveen Ramamoorthy, Jerry Sheehan, Larry Smarr, Charles V. Smith, Todd Smith, Michael Snyder, Srikanth Rapole, Sanjeeva Srivastava, Larissa Stanberry, Elizabeth Stewart, Stefano Toppo, Peter Uetz, Kenneth Verheggen, Brynn H. Voy, Louise Warnich, Steven W. Wilhelm, Gregory Yandl:
Toward More Transparent and Reproducible Omics Studies Through a Common Metadata Checklist and Data Publications. Big Data 1(4): 196-201 (2013) - [j32]Tom Scogland, Balaji Subramaniam, Wu-chun Feng:
The Green500 list: escapades to exascale. Comput. Sci. Res. Dev. 28(2-3): 109-117 (2013) - [j31]Kenneth S. Lee, Heshan Lin, Wu-chun Feng:
Performance characterization of data-intensive kernels on AMD Fusion architectures. Comput. Sci. Res. Dev. 28(2-3): 175-184 (2013) - [j30]Balaji Subramaniam, Wu-chun Feng:
GBench: benchmarking methodology for evaluating the energy efficiency of supercomputers. Comput. Sci. Res. Dev. 28(2-3): 221-230 (2013) - [j29]Mark K. Gardner, Paul Sathre, Wu-chun Feng, Gabriel Martinez:
Characterizing the challenges and evaluating the efficacy of a CUDA-to-OpenCL translator. Parallel Comput. 39(12): 769-786 (2013) - [c124]Jing Zhang, Heshan Lin, Pavan Balaji, Wu-chun Feng:
Optimizing Burrows-Wheeler Transform-Based Sequence Alignment on Multicore Architectures. CCGRID 2013: 377-384 - [c123]