Xing Cai

• Zhao, Max; Burchard, Luk Bjarne; Schroeder, Daniel Thilo; Langguth, Johannes & Cai, Xing (2024). iPuma: High-Performance Sequence Alignment on the Graphcore IPU. I Taufer, Michela; Hoefler, Torsten; Hammond, Jeff & Randles, Amanda (Red.), ISC High Performance 2024 Research Paper Proceedings. IEEE Press. ISSN 978-3-9826336-0-2. doi: 10.23919/ISC.2024.10528941.
• Sæternes, Erik Hide; Thune, Andreas; Rustad, Alf Birger; Skeie, Tor & Cai, Xing (2024). Automated parameter tuning with accuracy control for efficient reservoir simulations. Journal of Computational Science. ISSN 1877-7503. 75. doi: 10.1016/j.jocs.2023.102205. Fulltekst i vitenarkiv
• Thune, Andreas; Reinemo, Sven- Arne; Skeie, Tor & Cai, Xing (2023). Detailed modeling of heterogeneous and contention-constrained point-to-point MPI communication. IEEE Transactions on Parallel and Distributed Systems. ISSN 1045-9219. 34(5), s. 1580–1593. doi: 10.1109/TPDS.2023.3253881.
• Trotter, James David; Langguth, Johannes & Cai, Xing (2023). Targeting performance and user-friendliness: GPU-accelerated finite element computation with automated code generation in FEniCS. Parallel Computing. ISSN 0167-8191. 118. doi: 10.1016/j.parco.2023.103051. Fulltekst i vitenarkiv
• Burchard, Luk Bjarne; Hustad, Kristian Gregorius; Langguth, Johannes & Cai, Xing (2023). Enabling unstructured-mesh computation on massively tiled AI processors: An example of accelerating in silico cardiac simulation. Frontiers in Physics. ISSN 2296-424X. 11. doi: 10.3389/fphy.2023.979699. Fulltekst i vitenarkiv
• Telle, Åshild; Trotter, James David; Cai, Xing; Finsberg, Henrik Nicolay Topnes; Kuchta, Miroslav & Sundnes, Joakim [Vis alle 7 forfattere av denne artikkelen] (2023). A cell-based framework for modeling cardiac mechanics. Biomechanics and Modeling in Mechanobiology. ISSN 1617-7959. 22, s. 515–539. doi: 10.1007/s10237-022-01660-8. Fulltekst i vitenarkiv
• Hustad, Kristian Gregorius & Cai, Xing (2022). Resource-Efficient Use of Modern Processor Architectures For Numerically Solving Cardiac Ionic Cell Models. Frontiers in Physiology. ISSN 1664-042X. 13. doi: 10.3389/fphys.2022.904648. Fulltekst i vitenarkiv
• Trotter, James David; Cai, Xing & Funke, Simon Wolfgang (2022). On Memory Traffic and Optimisations for Low-order Finite Element Assembly Algorithms on Multi-core CPUs. ACM Transactions on Mathematical Software. ISSN 0098-3500. 48(2), s. 1–31. doi: 10.1145/3503925. Fulltekst i vitenarkiv
• Burchard, Luk; Cai, Xing & Langguth, Johannes (2021). iPUG for Multiple Graphcore IPUs: Optimizing Performance and Scalability of Parallel Breadth-First Search. I Sur, Chiranjib & Kothapalli, Kishore (Red.), 2021 IEEE 28th International Conference on High Performance Computing, Data, and Analytics (HiPC). IEEE (Institute of Electrical and Electronics Engineers). ISSN 978-1-6654-1016-8. s. 162–171. doi: 10.1109/HiPC53243.2021.00030. Fulltekst i vitenarkiv
• Thune, Andreas; Cai, Xing & Rustad, Alf Birger (2021). On the impact of heterogeneity-aware mesh partitioning and non-contributing computation removal on parallel reservoir simulations. Journal of Mathematics in Industry. ISSN 2190-5983. 11. doi: 10.1186/s13362-021-00108-5. Fulltekst i vitenarkiv
• Jæger, Karoline Horgmo; Hustad, Kristian Gregorius; Cai, Xing & Tveito, Aslak (2021). Efficient numerical solution of the EMI model representing the extracellular space (E), cell membrane (M) and intracellular space (I) of a collection of cardiac cells. Frontiers in Physics. ISSN 2296-424X. 8(579461). doi: 10.3389/fphy.2020.579461. Fulltekst i vitenarkiv
• Jæger, Karoline Horgmo; Hustad, Kristian Gregorius; Cai, Xing & Tveito, Aslak (2020). Operator Splitting and Finite Difference Schemes for Solving the EMI Model. I Tveito, Aslak; Mardal, Kent-Andre & Rognes, Marie (Red.), Modeling Excitable Tissue -- The EMI Framework. Springer. ISSN 978-3-030-61156-9. s. 44–55. doi: 10.1007/978-3-030-61157-6_4.
• Trotter, James David; Langguth, Johannes & Cai, Xing (2020). Cache simulation for irregular memory traffic on multi-core CPUs: Case study on performance models for sparse matrix–vector multiplication. Journal of Parallel and Distributed Computing. ISSN 0743-7315. 144, s. 189–205. doi: 10.1016/j.jpdc.2020.05.020.
• Jarvis, Chad; Lines, Glenn Terje; Langguth, Johannes; Nakajima, Kengo & Cai, Xing (2019). Combining algorithmic rethinking and AVX-512 intrinsics for efficient simulation of subcellular calcium signaling. I Rodrigues, João M. F.; Cardoso, Pedro; Monteiro, Jânio; Lam, Roberto; Krzhizhanovskaya, Valeria V.; Lees, Michael H.; Dongarra, Jack & Sloot, Peter M.A. (Red.), Proceedings of 19th International Conference on Computational Science, ICCS2019, Part V. Springer. ISSN 978-3-030-22749-4. s. 681–687. doi: 10.1007/978-3-030-22750-0_66.
• Lagraviere, Jeremie Alexandre Emilien; Langguth, Johannes; Prugger, Martina; Einkemmer, Lukas; Ha, Hoai Phuong & Cai, Xing (2019). Performance optimization and modeling of fine-grained irregular communication in UPC. Scientific Programming. ISSN 1058-9244. 2019:6825728, s. 1–20. doi: 10.1155/2019/6825728. Fulltekst i vitenarkiv
• Langguth, Johannes; Cai, Xing & Sourouri, Mohammed (2018). Memory bandwidth contention: Communication vs computation Tradeoffs in supercomputers with multicore architectures. I Li, Mo & Tan, Kian-Lee (Red.), Proceedings 2018 IEEE 24th International Conference on Parallel and Distributed Systems ICPADS 2018. IEEE Sarnoff Symposium. ISSN 978-1-5386-7308-9. s. 497–506. doi: 10.1109/PADSW.2018.8644601.
• Paulsen, Geir; Clark, Stuart R; Nordmoen, Bjørn; Nenakhov, Sergey; Andersson, Aron & Cai, Xing [Vis alle 7 forfattere av denne artikkelen] (2017). Automated Translation of MATLAB Code to C++ with Performance and Traceability. I Rückemann, Claus-Peter & Vucinic, D (Red.), Proceedings of the Eleventh International Conference on Advanced Engineering Computing and Applications in Sciences (ADVCOMP 2017). International Academy, Research and Industry Association (IARIA). ISSN 978-1-61208-599-9. s. 50–55.
• Langguth, Johannes; Jarvis, Chad & Cai, Xing (2017). Porting tissue-scale cardiac simulations to the knights landing platform. Lecture Notes in Computer Science (LNCS). ISSN 0302-9743. 10524 LNCS, s. 376–388. doi: 10.1007/978-3-319-67630-2_28.
• Paulsen, Geir; Feinberg, Jonathan; Cai, Xing; Nordmoen, Bjørn & Dahle, Hans Petter (2016). Matlab2cpp: A Matlab-to-C++ code translator, 2016 11th System of Systems Engineering Conference (SoSE). IEEE conference proceedings. ISSN 978-1-4673-8727-9. doi: 10.1109/SYSOSE.2016.7542966.
• Langguth, Johannes; Lan, Qiang; Gaur, Namit; Cai, Xing; Wen, Mei & Zhang, Chun-Yuan (2016). Enabling tissue-scale cardiac simulations using heterogeneous computing on tianhe-2. I Liao, Xiaofei; Lovas, Robert; Shen, Xipeng & Zheng, Ran (Red.), IEEE 22nd International Conference on Parallel and Distributed Systems (ICPADS). IEEE (Institute of Electrical and Electronics Engineers). ISSN 978-1-5090-4457-3. s. 843–852. doi: 10.1109/ICPADS.2016.0114.
• Langguth, Johannes; Lan, Qiang; Gaur, Namit & Cai, Xing (2016). Accelerating Detailed Tissue-Scale 3D Cardiac Simulations Using Heterogeneous CPU-Xeon Phi Computing. International journal of parallel programming. ISSN 0885-7458. 45(5), s. 1236–1258. doi: 10.1007/s10766-016-0461-2. Vis sammendrag

  We investigate heterogeneous computing, which involves both multicore CPUs and manycore Xeon Phi coprocessors, as a new strategy for computational cardiology. In particular, 3D tissues of the human cardiac ventricle are studied with a physiologically realistic model that has 10,000 calcium release units per cell and 100 ryanodine receptors per release unit, together with tissue-scale simulations of the electrical activity and calcium handling. In order to attain resource-efficient use of heterogeneous computing systems that consist of both CPUs and Xeon Phis, we first direct the coding effort at ensuring good performance on the two types of compute devices individually. Although SIMD code vectorization is the main theme of performance programming, the actual implementation details differ considerably between CPU and Xeon Phi. Moreover, in addition to combined OpenMP+MPI programming, a suitable division of the cells between the CPUs and Xeon Phis is important for resource-efficient usage of an entire heterogeneous system. Numerical experiments show that good resource utilization is indeed achieved and that such a heterogeneous simulator paves the way for ultimately understanding the mechanisms of arrhythmia. The uncovered good programming practices can be used by computational scientists who want to adopt similar heterogeneous hardware platforms for a wide variety of applications.

• Sourouri, Mohammed; Scott, Baden & Cai, Xing (2016). Panda: A Compiler Framework for Concurrent CPU+GPU Execution of 3D Stencil Computations on GPU-accelerated Supercomputers. International journal of parallel programming. ISSN 0885-7458. 45(3), s. 711–729. doi: 10.1007/s10766-016-0454-1. Vis sammendrag

  We present a new compiler framework for truly heterogeneous 3D stencil computation on GPU clusters. Our framework consists of a simple directive-based programming model and a tightly integrated source-to-source compiler. Annotated with a small number of directives, sequential stencil C codes can be automatically parallelized for large-scale GPU clusters. The most distinctive feature of the compiler is its capability to generate hybrid MPI + CUDA + OpenMP code that uses concurrent CPU + GPU computing to unleash the full potential of powerful GPU clusters. The auto-generated hybrid codes hide the overhead of various data motion by overlapping them with computation. Test results on the Titan supercomputer and the Wilkes cluster show that auto-translated codes can achieve about 90 % of the performance of highly optimized handwritten codes, for both a simple stencil benchmark and a real-world application in cardiac modeling. The user-friendliness and performance of our domain-specific compiler framework allow harnessing the full power of GPU-accelerated supercomputing without painstaking coding effort.

• Lagraviere, Jeremie Alexandre Emilien; Langguth, Johannes; Sourouri, Mohammed; Ha, Hoai Phuong & Cai, Xing (2016). On the performance and energy efficiency of the PGAS programming model on multicore architectures. I Fox, Geoffrey C. & Nygård, Mads (Red.), Proceedings of the 14th IEEE International Conference on High Performance Computing & Simulation (HPCS 2016). IEEE conference proceedings. ISSN 978-1-5090-2088-1. s. 800–807. doi: 10.1109/HPCSim.2016.7568416. Fulltekst i vitenarkiv
• Zhang, Wei & Cai, Xing (2016). Solving 3D Time-Fractional Diffusion Equations by High-Performance Parallel Computing. Fractional Calculus and Applied Analysis. ISSN 1311-0454. 19(1), s. 140–160. doi: 10.1515/fca-2016-0008.
• Cai, Xing (2015). Parallel Computing. I Engquist, Björn (Red.), Encyclopedia of Applied and Computational Mathematics. Springer. ISSN 978-3-540-70528-4. s. 1129–1132. doi: 10.1007/978-3-540-70529-1_424.
• Sourouri, Mohammed; Gillberg, Tor; Baden, Scott & Cai, Xing (2015). Effective multi-GPU communication using multiple CUDA streams and threads. Proceedings of the International Conference on Parallel and Distributed Systems. ISSN 1521-9097. 2015-April, s. 981–986. doi: 10.1109/PADSW.2014.7097919.
• Langguth, Johannes & Cai, Xing (2015). Heterogeneous CPU-GPU computing for the finite volume method on 3D unstructured meshes. Proceedings of the International Conference on Parallel and Distributed Systems. ISSN 1521-9097. 2015-April, s. 191–199. doi: 10.1109/PADSW.2014.7097808.
• Sourouri, Mohammed; Langguth, Johannes; Spiga, Filippo; Baden, Scott & Cai, Xing (2015). CPU+GPU Programming of Stencil Computations for Resource-Efficient Use of GPU Clusters. I Plessl, Christian (Red.), Proceedings of the 2015 IEEE 18th International Conference on Computational Science and Engineering. IEEE (Institute of Electrical and Electronics Engineers). ISSN 978-1-4673-8297-7. s. 17–26. doi: 10.1109/CSE.2015.33.
• Lan, Qiang; Gaur, Namit; Langguth, Johannes & Cai, Xing (2015). Towards Detailed Tissue-Scale 3D Simulations of Electrical Activity and Calcium Handling in the Human Cardiac Ventricle. I Wang, Guojun; Zomaya, Albert; Perez, Gregorio Martinez & Li, Kenli (Red.), Algorithms and Architectures for Parallel Processing. Springer. ISSN 978-3-319-27137-8. s. 79–92. doi: 10.1007/978-3-319-27137-8_7.
• Dong, Xinnan; Wen, Mei; Chai, Jun; Cai, Xing; Zhao, Mandan & Zhang, Chunyuan (2015). Communication-hiding programming for clusters with multi-coprocessor nodes. Concurrency and Computation. ISSN 1532-0626. 27(16), s. 4172–4185. doi: 10.1002/cpe.3507.
• Langguth, Johannes; Sourouri, Mohammed; Lines, Glenn Terje; Baden, Scott & Cai, Xing (2015). Scalable heterogeneous CPU-GPU computations for unstructured tetrahedral meshes. IEEE Micro. ISSN 0272-1732. 35(4), s. 6–15. doi: 10.1109/MM.2015.70.
• Krishnasamy, Ezhilmathi; Sourouri, Mohammed & Cai, Xing (2015). Multi-GPU implementations of parallel 3D sweeping algorithms with application to geological folding. Procedia Computer Science. ISSN 1877-0509. 51, s. 1494–1503. doi: 10.1016/j.procs.2015.05.339.
• Huang, Dafei; Xun, Changqing; Wu, Nan; Wen, Mei; Zhang, Chunyuan & Cai, Xing [Vis alle 7 forfattere av denne artikkelen] (2015). Enabling a uniform OpenCL device view for heterogeneous platforms. IEICE transactions on information and systems. ISSN 0916-8532. E98-D(4), s. 812–823. doi: 10.1587/transinf.2014EDP7244.
• Su, Huayou; Cai, Xing; Wen, Mei & Zhang, Chunyuan (2015). An analytical GPU performance model for 3D stencil computations from the angle of data traffic. The Journal of Supercomputing. ISSN 0920-8542. 71(7), s. 2433–2453. doi: 10.1007/s11227-015-1392-1. Vis sammendrag

  The achievable GPU performance of many scientific computations is not determined by a GPU’s peak floating-point rate, but rather how fast data are moved through different stages of the entire memory hierarchy. We take low-order 3D stencil computations as a representative class to study the reachable GPU performance from the angle of data traffic. Specifically, we propose a simple analytical model to estimate the execution time based on quantifying the data traffic volume at three stages: (1) between registers and on-streaming multiprocessor (SMX) storage, (2) between on-SMX storage and L2 cache, (3) between L2 cache and GPU’s device memory. Three associated granularities are used: a CUDA thread, a thread block, and a set of simultaneously active thread blocks. For four chosen 3D stencil computations, NVIDIA’s profiling tools are used to verify the accuracy of the quantified data traffic volumes, by examining a large number of executions with different problem sizes and thread block configurations. Moreover, by introducing an imbalance coefficient, together with the known realistic memory bandwidths, we can predict the execution time usage based on the quantified data traffic volumes. For the four 3D stencils, the average error of the time predictions is 6.9 % for a baseline implementation approach, whereas for a blocking implementation approach the average prediction error is 9.5 %.

• Langguth, Johannes; Wu, Nan; Chai, Jun & Cai, Xing (2015). Parallel performance modeling of irregular applications in cell-centered finite volume methods over unstructured tetrahedral meshes. Journal of Parallel and Distributed Computing. ISSN 0743-7315. 76, s. 120–131. doi: 10.1016/j.jpdc.2014.10.005.
• Chai, Jun; Hake, Johan Elon; Wu, Nan; Wen, Mei; Cai, Xing & Lines, Glenn Terje [Vis alle 10 forfattere av denne artikkelen] (2015). Towards simulation of subcellular calcium dynamics at nanometre resolution. The international journal of high performance computing applications. ISSN 1094-3420. 29(1), s. 51–63. doi: 10.1177/1094342013514465.
• Huang, Dafei; Wen, Mei; Xun, Changqing; Chen, Dong; Cai, Xing & Qiao, Yuran [Vis alle 8 forfattere av denne artikkelen] (2014). Automated Transformation of GPU-Specific OpenCL Kernels Targeting Performance Portability on Multi-Core/Many-Core CPUs. I Silva, Fernando (Red.), Euro-Par 2014 Parallel Processing. Springer. ISSN 978-3-319-09872-2. s. 210–221. doi: 10.1007/978-3-319-09873-9_18.
• Dong, Xinnan; Chai, Jun; Yang, Jing (NUDT); Wen, Mei; Wu, Nan & Cai, Xing [Vis alle 8 forfattere av denne artikkelen] (2014). Utilizing Multiple Xeon Phi Coprocessors on One Compute Node. I Sun, Xian-he (Red.), Algorithms and Architectures for Parallel Processing. Springer. ISSN 978-3-319-11193-3. s. 68–81. doi: 10.1007/978-3-319-11194-0_6.
• Zhang, Wei; Wei, Wenjie & Cai, Xing (2014). Performance modeling of serial and parallel implementations of the fractional Adams-Bashforth-Moulton method. Fractional Calculus and Applied Analysis. ISSN 1311-0454. 17(3), s. 617–637. doi: 10.2478/s13540-014-0189-x.
• Zhang, Wei; Cai, Xing & Holm, Sverre (2014). Time-fractional heat equations and negative absolute temperatures. Computers and Mathematics with Applications. ISSN 0898-1221. 67(1), s. 164–171. doi: 10.1016/j.camwa.2013.11.007.
• Wen, Mei; Su, Huayou; Wei, Wenjie; Wu, Nan; Cai, Xing & Zhang, Chunyuan (2014). High efficient sedimentary basin simulations on hybrid CPU-GPU clusters. Cluster Computing. ISSN 1386-7857. 17(2), s. 359–369. doi: 10.1007/s10586-013-0300-9.
• Su, Huayou; Wu, Nan; Wen, Mei; Zhang, Chunyuan & Cai, Xing (2013). On the GPU-CPU Performance Portability of OpenCL for 3D Stencil Computations, 2013 International Conference on Parallel and Distributed Systems (ICPADS). IEEE (Institute of Electrical and Electronics Engineers). ISSN 978-1-4799-2081-5. s. 78–85. doi: 10.1109/ICPADS.2013.23.
• Langguth, Johannes; Wu, Nan; Chai, Jun & Cai, Xing (2013). On the GPU performance of cell-centered finite volume method over unstructured tetrahedral meshes. I Tumeo, Antonino; Feo, John; Villa, Oreste & Secchi, Simone (Red.), Proceedings of the 3rd Workshop on Irregular Applications: Architectures and Algorithms. ACM Publications. ISSN 978-1-4503-2503-5. doi: 10.1145/2535753.2535765.
• Wei, Wenjie; Clark, Stuart R; Su, Huayou; Wen, Mei & Cai, Xing (2013). Balancing efficiency and accuracy for sediment transport simulations. Computational Science & Discovery. ISSN 1749-4680. 6(1). doi: 10.1088/1749-4699/6/1/015011.
• Chai, Jun; Wen, Mei; Wu, Nan; Huang, Dafei; Yang, Jing (NUDT) & Cai, Xing [Vis alle 8 forfattere av denne artikkelen] (2013). Simulating cardiac electrophysiology in the era of GPU-cluster computing. IEICE transactions on information and systems. ISSN 0916-8532. E96-D(12), s. 2587–2595. doi: 10.1587/transinf.E96.D.2587.
• Chai, Jun; Su, Huayou; Wen, Mei; Cai, Xing; Wu, Nan & Zhang, Chunyuan (2013). Resource-efficient utilization of CPU/GPU-based heterogeneous supercomputers for Bayesian phylogenetic inference. The Journal of Supercomputing. ISSN 0920-8542. 66(1), s. 364–380. doi: 10.1007/s11227-013-0911-1.
• Su, Huayou; Wu, Nan; Wen, Mei; Zhang, Chunyuan & Cai, Xing (2013). Performance of sediment transport simulations on NVIDIA’s Kepler architecture. Procedia Computer Science. ISSN 1877-0509. 18, s. 1275–1281. doi: 10.1016/j.procs.2013.05.294. Fulltekst i vitenarkiv
• Su, Huayou; Wu, Nan; Wen, Mei; Zhang, Chunyuan & Cai, Xing (2013). On the GPU performance of 3D stencil computations implemented in OpenCL. I Kunkel, Julian Martin; Ludwig, Thomas & Meuer, Hans Werner (Red.), Proceedings of 28th International Supercomputing Conference, ISC 2013. Springer. ISSN 978-3-642-38749-4. s. 125–135. doi: 10.1007/978-3-642-38750-0_10.
• Unat, Didem; Zhou, Jun (UCSD); Cui, Yifeng; Baden, Scott & Cai, Xing (2012). Accelerating a 3D finite-difference earthquake simulation with a C-to-CUDA translator. Computing in science & engineering (Print). ISSN 1521-9615. 14(3), s. 48–59. doi: 10.1109/MCSE.2012.44.
• Wen, Mei; Su, Huayou; Wei, Wenjie; Wu, Nan; Cai, Xing & Zhang, Chunyuan (2012). Using 1000+ GPUs and 10000+ CPUs for sedimentary basin simulations, 2012 IEEE International Conference on Cluster Computing, CLUSTER 2012. IEEE (Institute of Electrical and Electronics Engineers). ISSN 978-1-4673-2422-9. s. 27–35. doi: 10.1109/cluster.2012.37.
• Gillberg, Tor; Sourouri, Mohammed & Cai, Xing (2012). A New Parallel 3D Front Propagation Algorithm for Fast Simulation of Geological folds. Procedia Computer Science. ISSN 1877-0509. 9, s. 947–955. doi: 10.1016/j.procs.2012.04.101.
• Wei, Wenjie; al-Khayat, Omar & Cai, Xing (2011). An OpenMP-enabled parallel simulator for particle transport in fluid flows. Procedia Computer Science. ISSN 1877-0509. 4, s. 1475–1484. doi: 10.1016/j.procs.2011.04.160.
• Didem, Unat; Cai, Xing & Baden, Scott (2011). Mint: Realizing CUDA performance in 3D stencil methods with annotated C. I Lowenthal, David; de Supinski,, Bronis R. & McKee, Sally A. (Red.), Proceedings of the 25th International Conference on Supercomputing (ICS'11). ACM Publications. ISSN 978-1-4503-0102-2. s. 214–224. doi: 10.1145/1995896.1995932. Vis sammendrag

  We present Mint, a programming model that enables the non-expert to enjoy the performance benefits of hand coded CUDA without becoming entangled in the details. Mint targets stencil methods, which are an important class of scientific applications. We have implemented the Mint programming model with a source-to-source translator that generates optimized CUDA C from traditional C source. The translator relies on annotations to guide translation at a high level. The set of pragmas is small, and the model is compact and simple. Yet, Mint is able to deliver performance competitive with painstakingly hand-optimized CUDA. We show that, for a set of widely used stencil kernels in two and three dimensions, Mint realized 80% of the performance obtained from aggressively optimized CUDA on the 200 series NVIDIA GPUs. Our optimizations target three dimensional kernels, which present a daunting array of optimizations.

• Hanslien, Monica; Artebrant, Robert; Tveito, Aslak; Lines, Glenn Terje & Cai, Xing (2011). STABILITY OF TWO TIME-INTEGRATORS FOR THE ALIEV-PANFILOV SYSTEM. International Journal of Numerical Analysis & Modeling. ISSN 1705-5105. 8(3), s. 427–442.
• Yeh, J.T,-C.; Cai, Xing; Langtangen, Hans Petter; Zhu, J & Chuen-F, Ni (2010). Parallel computing engines for subsurface imaging technologies. I Parashar, M. & Li, X (Red.), Advanced Computational Infrastructures for Parallel and Distributed Adaptive Applications. John Wiley & Sons. ISSN 978-0-470-07294-3. s. 29–43.
• Nilsen, Jon Kerr; Cai, Xing; Høyland, Bjørn & Langtangen, Hans Petter (2010). Simplifying the parallelization of scientific codes by a function-centric approach in Python. Computational Science & Discovery. ISSN 1749-4680. 3. doi: 10.1088/1749-4699/3/1/015003.
• Logg, Anders Bernhard; Langtangen, Hans Petter & Cai, Xing (2010). Past and Future Perspectives on Scientific Software. I Tveito, Aslak; Bruaset, Are Magnus & Lysne, Olav (Red.), Simula Research Laboratory - by thinking constantly about it. Springer. ISSN 978-3-642-01155-9. s. 321–362.
• Zhu, JF; Cai, Xing & Yeh, TCJ (2009). Analysis of tracer tomography using temporal moments of tracer breakthrough curves. Advances in Water Resources. ISSN 0309-1708. 32(3), s. 391–400. doi: 10.1016/j.advwatres.2008.12.001.
• Nielsen, Bjørn Fredrik; Cai, Xing; Sundnes, Joakim & Tveito, Aslak (2009). Towards a computational method for imaging the extracellular potassium concentration during regional ischemia. Mathematical Biosciences. ISSN 0025-5564. 220(2), s. 118–130. doi: 10.1016/j.mbs.2009.05.004.
• Bouhmala, Noureddine & Cai, Xing (2008). A Mulitlevel Greedy Algorithm for the Satisfiability Problem, Greedy Algorithms. IN-TECH. s. 39–54.
• Bouhmala, N & Cai, Xing (2008). A Multilevel Greedy Algorithm for the Satisfiability Problem. I Bednorz, Witold (Red.), Advances in Greedy Algorithms. N-TECH Education and Publishing. ISSN 978-953-7619-27-5. s. 39–54.
• Cai, Xing & Bouhmala, Noureddine (2007). A unified framework of multi-objective cost functions for partitioning unstructured finite element meshes. Applied Mathematical Modelling. ISSN 0307-904X. 31(9), s. 1711–1728. Vis sammendrag

  Good performance of parallel finite element computations on unstructured meshes requires high-quality mesh partitioning. Such a decomposition task is normally done by a graph-based partitioning approach. However, the main shortcoming of graph partitioning algorithms is that minimizing the so-called edge cut is not entirely the same as minimizing the communication overhead. This paper thus proposes a unified framework of multi-objective cost functions, which take into account several factors that are not captured by the graph-based partitioning approach. Freely adjustable weighting parameters in the framework also promote a flexible treatment of different optimization objectives. A greedy-style post-improvement procedure is designed to use these cost functions to improve the quality of subdomain meshes arising from the graph-based partitioning approach. Both serial and parallel implementation of the post-improvement procedure have been done. Numerical experiments show that communication overhead can indeed be reduced by this improvement procedure, thereby increasing the performance of parallel finite element computations. (C) 2006 Elsevier Inc. All rights reserved.

• Haga, J.; Bruaset, Are Magnus; Cai, Xing; Langtangen, Hans Petter; Osnes, Harald & Skogseid, J. (2007). Parallelisation and numerical performance of a 3D model for coupled deformation, fluid flow and heat transfer in sedimentary basins. I Skallerud, B & Andersson, H. I. (Red.), MekIT'07. Tapir Akademisk Forlag. ISSN 978-82-519-2235-7. s. 151–162.
• Cai, Xing; Nielsen, Bjørn Fredrik & Tveito, Aslak (2007). A note on the efficiency of the conjugate gradient method for a class of time-dependent problems. Numerical Linear Algebra with Applications. ISSN 1070-5325. 14(5), s. 459–467. doi: 10.1002/nla.527.
• Cai, Xing & Bouhmala, N (2007). A unified framework of multi-objective cost functions for partitioning unstructured finite element meshes. Applied Mathematical Modelling. ISSN 0307-904X. 31. doi: 10.1016/j.apm.2006.06.007.
• Nielsen, Bjørn Fredrik; Cai, Xing & Lysaker, Ola Marius (2007). On the possibility for computing the transmembrane potential in the heart with a one shot method: An inverse problem. Mathematical Biosciences. ISSN 0025-5564. 210(2), s. 523–553. doi: 10.1016/j.mbs.2007.06.003.
• Cai, Xing & Langtangen, Hans Petter (2007). Making hybrid tsunami simulators in a parallel software framework. Lecture Notes in Computer Science (LNCS). ISSN 0302-9743. 4699, s. 686–693.
• Cai, Xing; Pedersen, Geir Kleivstul; Langtangen, Hans Petter & Glimsdal, Sylfest (2006). Parallel Simulation of Tsunamis Using a Hybrid Software Approach. I Joubert, G. R.; Peters, F. J.; Tirado, P; Nagel, W. E.; Plata, O. & Zapata, E. (Red.), Parallel Computing: Current and Future Issues of Highe End Computing. John von Neumann Institute for Computing. ISSN 3-00-017352-8. s. 383–390. Vis sammendrag

  Parallel Simulation of Tsunamis Using a Hybrid Software Approach

• Cai, Xing (2006). Improving the performance of large-scale unstructured PDE applications. Lecture Notes in Computer Science (LNCS). ISSN 0302-9743. 3732, s. 699–708.
• Sundnes, Joakim; Nielsen, Bjørn Fredrik; Mardal, Kent-Andre; Cai, Xing; Lines, Glenn Terje & Tveito, Aslak (2006). On the computational complexity of the bidomain and the monodomain models of electrophysiology. Annals of Biomedical Engineering. ISSN 0090-6964. 34(7), s. 1088–1097.
• Cai, Xing & Langtangen, Hans Petter (2005). Parallelizing PDE solvers using the Python programming language. I Bruaset, Are Magnus & Tveito, Aslak (Red.), Numerical Solution of Partial Differential Equations on Parallel Computers. Springer. ISSN 3-540-29076-1.

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• Tveito, Aslak; Langtangen, Hans Petter; Nielsen, Bjørn Fredrik & Cai, Xing (2010). Elements of scientific computing. Springer. ISBN 9783642112980. 459 s.
• Sundnes, Joakim; Lines, Glenn Terje; Cai, Xing; Nielsen, Bjørn Fredrik; Mardal, Kent-Andre & Tveito, Aslak (2006). Computing the electrical activity in the heart. Springer. ISBN 978-3-540-33432-3. 311 s.

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• Cai, Xing (2023). Quality control and innovation in computing and networking using the eX3 testbed.
• Cai, Xing (2023). Towards high-performance unstructured-mesh computations.
• Bruaset, Are Magnus; Cai, Xing; Desprez, Frédéric & Parsons, Mark (2023). Editorial: Heterogeneous computing in physics-based models. Frontiers in Physics. ISSN 2296-424X. 11. doi: 10.3389/fphy.2023.1320450.
• Langguth, Johannes; Gaur, Namit; Arevalo, Hermenegild; Jarvis, Chad; Altanaite, Neringa & Lan, Qiang [Vis alle 7 forfattere av denne artikkelen] (2020). Towards detailed Organ-Scale Simulations in Cardiac Electrophysiology.
• Hustad, Kristian Gregorius; Cai, Xing; Langguth, Johannes & Arevalo, Hermenegild (2020). Efficient simulations of patient-specific electrical heart activity on the DGX-2.
• Trotter, James David; Cai, Xing; Funke, Simon Wolfgang & Langguth, Johannes (2019). Compiling finite element variational forms for GPU-based assembly.
• Thune, Andreas & Cai, Xing (2019). Balancing the numerical and parallel performance for reservoir simulations.
• Cai, Xing (2019). Unstructured computational meshes and data locality.
• Cai, Xing (2019). Heterogeneous computing for cardiac electrophysiology.
• Langguth, Johannes; Arevalo, Hermenegild; Hustad, Kristian Gregorius & Cai, Xing (2019). Towards detailed real-time simulations of cardiac arrhythmia.
• Langguth, Johannes; Hermenegild, Arevalo; Jarvis, Chad & Cai, Xing (2018). Towards Detailed Organ-Scale Simulations in Cardiac Electrophysiology.
• Cai, Xing (2018). Heterogeneous Computing: Programming, Performance and Applications.
• Trotter, James David; Langguth, Johannes & Cai, Xing (2018). Quantifying data traffic of sparse matrix-vector multiplication in a multi-level memory hierarchy.
• Cai, Xing (2018). Education in HPC and Data Science at Simula Research Lab and UiO.
• Thune, Andreas & Cai, Xing (2018). Unstructured mesh partitioning in the presence of strong coefficient heterogeneity.
• Cai, Xing & Langguth, Johannes (2017). Accelerated high-performance computing for computational cardiac electrophysiology.
• Cai, Xing (2017). OpenMP Programming.
• Lagraviere, Jeremie Alexandre Emilien; Langguth, Johannes; Sourouri, Mohammed; Ha, Hoai Phuong & Cai, Xing (2016). On the performance and energy efficiency of the PGAS programming model on multicore architectures.
• Chatelin, Simon; Lambert, Simon; Jugé, Lauriane; Cai, Xing; Näsholm, Sven Peter & Vilgrain, Valérie [Vis alle 12 forfattere av denne artikkelen] (2012). Measured elasticity and its frequency dependence are sensitive to tissue microarchitecture in MR Elastography.
• Bouhmala, Noureddine & Cai, Xing (2009). A Multilevel Approach for the Satisfiability Problem. ISAST Transactions on Computers and Intelligent Systems. ISSN 1798-2448. 2(1), s. 29–37. Vis sammendrag

  A large number of problems that occur in knowledge-representation, learning, VLSI design,and other areas of artificial intelligence are essentially satisfiability problems. The satisfiability problem refers to the task of finding a true assignment that makes a boolean expression true. The growing need for more efficient and scalable algorithms have led to the development of several SAT solvers. In this paper, we introduce a multilevel approach combining the multilevel paradigm with the GSAT greedy algorithm for solving the satisfiability problem. We present a comparative analysis of the new algorithm's performance using a benchmark set containing randomized and structured problems from various domains. SAT, GSAT, multilevel optimization, combinatorial optimization

• Cai, Xing (2006). Parallelizing serial PDE software using a generic approach.
• Cai, Xing (2006). Simulating Tsunamis on Parallel Computers.
• Alnæs, Martin Sandve; Bruaset, Are Magnus; Cai, Xing; Langtangen, Hans Petter; Mardal, Kent-Andre & Moe, Halvard [Vis alle 8 forfattere av denne artikkelen] (2006). High-performance computing in Python.
• Cai, Xing & Langtangen, Hans Petter (2006). Making hybrid tsunami simulators in a parallel software framework.
• Lagraviere, Jeremie Alexandre Emilien; Prugger, Martina; Einkemmer, Lukas; Langguth, Johannes; Ha, Hoai Phuong & Cai, Xing (2016). Implementing and optimizing a Sparse Matrix-Vector Multiplication with UPC. Institutt for informatikk Tromsø Tromsø. Fulltekst i vitenarkiv
• Lagraviere, Jeremie; Ha, Hoai Phuong & Cai, Xing (2015). Evaluation of the power efficiency of UPC, OpenMP and MPI. Institutt for informatikk Tromsø. Fulltekst i vitenarkiv
• Osnes, Harald; Cai, Xing; Bruaset, Are Magnus & Langtangen, Hans Petter (2006). Simulation of Deformation and Heat Flow in Sedimentary Basins, Project Report. Simula Research Laboratory.

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