Laxmikant Kale




Laxmikant Kalé received his Ph.D. from the State University of New York at Stony Brook in 1985. He is a professor in the U of I Department of Computer Science and a part-time faculty member in the Beckman Institute Theoretical and Computational Biophysics group. His primary research interests include parallel computing with emphasis on irregular and dynamic applications, and development of parallel objects technology.


Kalé's work is aimed at improving performance and productivity in parallel programming. He pioneered the development of object-based parallel programming (via the Charm++ system, and its precursor, the chare kernel).

Although a large number of early parallel applications have been highly regular in structure, and could be parallelized easily using extant approaches, many emerging applications manifest irregular structure as well as dynamically changing structure. Development of effective techniques for efficient parallelization of such applications, without excessive programming effort, is a primary goal of his research.

Data-driven objects, embodied in Charm++, provide an effective substrate for such techniques. A programmer divides the parallel competition into a number of interacting objects, while the Charm++ system manages the placement and scheduling of these objects, migrating them when necessary. This creates an almost optimal division of labor between the human programmer and the automated runtime system, each being responsible for the part it can do best.

Kalé is engaged in a collaborative research project at the Beckman Institute with professors Schulten and Skeel. A specific research project involves development of a parallel molecular dynamics program, named NAMD2. Using Charm++, and other techniques developed in Kalé's research, this program runs on all available parallel machines and workstation clusters, and is in production use by scientists. This program has demonstrated highest speedups, 180 on 220 processors, of any production-quantity molecular dynamics program to date. Kalé is also involved in the development of a synchronous/asynchronous collaboratory for molecular dynamics. More information about his research can be found at


  • 2016
    • Bock, N.; Challacombe, M.; Kale, L. V., Solvers for O(N) Electronic Structure in the Strong Scaling Limit. Siam Journal on Scientific Computing 2016, 38, (1), C1-C21, DOI:10.1137/140974602.
  • 2015
    • Totoni, E.; Jain, N.; Kale, L., Power Management of Extreme-Scale Networks with on/Off Links in Runtime Systems. ACM Transactions on Parallel Computing 2015, 1, (2), DOI:10.1145/2687001.

    • Menon, H.; Wesolowski, L.; Zheng, G.; Jetley, P.; Kale, L.; Quinn, T.; Governato, F., Adaptive Techniques for Clustered N-Body Cosmological Simulations. Computational Astrophysics and Cosmology 2015, 2, (1), DOI:10.1186/s40668-015-0007-9.

    • Meneses, E.; Kale, L., Camel: Collective-Aware Message Logging. The Journal of Supercomputing 2015, 71, (7), 2516-2538.

    • Acun, B.; Jain, N.; Bhatele, A.; Mubarak, M.; Carothers, C. D.; Kale, L. V., Preliminary Evaluation of a Parallel Trace Replay Tool for HPC Network Simulations. Euro-Par 2015: Parallel Processing Workshops 2015, 9523, 417-429, DOI:10.1007/978-3-319-27308-2_34.
    • Meneses, E.; Ni, X.; Zheng, G. B.; Mendes, C. L.; Kale, L. V., Using Migratable Objects to Enhance Fault Tolerance Schemes in Supercomputers. IEEE Transactions on Parallel and Distributed Systems 2015, 26, (7), 2061-2074, DOI:10.1109/Tpds.2014.2342228.
  • 2014
    • Totoni, E.; Heath, M. T.; Kale, L. V., Structure-Adaptive Parallel Solution of Sparse Triangular Linear Systems. Parallel Computing 2014, 40, (9), 454-470, DOI:10.1016/j.parco.2014.06.006.

    • Meneses, E.; Sarood, O.; Kale, L. V., Energy Profile of Rollback-Recovery Strategies in High Performance Computing. Parallel Computing 2014, 40, (9), 536-547,DOI:10.1016/j.parco.2014.03.005.

    • Meneses, E.; Ni, X.; Zheng, G.; Mendes, C.; Kale, L., Using Migratable Objects to Enhance Fault Tolerance Schemes in Supercomputers. IEEE Transactions on Parallel and Distributed Systems (TPDS) 2014, 26, (7), 2061-2074.

    • Jain, N.; Bhatele, A.; Yeom, J. S.; Adams, M.; Miniati, F.; Mei, C.; Kale, L., On Interoperation among User-Driven and System-Driven Parallel Languages. University of Illinois - Computer Science Research and Tech Reports 2014.

    • Gupta, A.; Faraboschi, P.; Gioachin, F.; Kale, L.; Kaufmann, R.; Lee, B. S.; March, V.; Milojicic, D.; Suen, C. H., Evaluating and Improving the Performance and Scheduling of HPC Applications in Cloud. IEEE Transactions on Cloud Computing 2014, PP, (99).

    • Capello, F.; Geist, A.; Gropp, W.; Kale, L.; Kramer, B.; Snir, M., Toward Exascale Resilience: 2014 Update. Supercomputing Frontiers And Innovations 2014, 1, (1), DOI:10.14529/jsfi140101.

  • 2013
    • Gupta, A.; Sarood, O.; Kale, L. V.; Milojicic, D. Improving HPC Application Performance in Cloud through Dynamic Load Balancing. 13th IEEE/ACM International Symposium on Cluster, Cloud, and Grid Computing. IEEE: New York, 2013, 402-409.

    • Lifflander, J.; Krishnamoorthy, S.; Kale, L. V., Steal Tree: Low-Overhead Tracing of Work Stealing Schedulers. ACM Sigplan Notices 2013, 48, (6), 507-518.

    • Lifflander, J.; Miller, P.; Kale, L. V., Adoption Protocols for Fanout-Optimal Fault-Tolerant Termination Detection. ACM Sigplan Notices 2013, 48, (8), 13-22, DOI: 10.1145/2517327.2442519.

  • 2012
    • Sarood, O.; Miller, P.; Totoni, E.; Kale, L. V., "Cool" Load Balancing for High Performance Computing Data Centers. IEEE Transactions on Computers 2012, 61, (12), 1752-1764.

    • Miller, P.; Becker, A.; Kale, L., Using Shared Arrays in Message-Driven Parallel Programs. Parallel Computing 2012, 38, (1-2), 66-74.

  • 2011
    • Zheng, G. B.; Bhatele, A.; Meneses, E.; Kale, L. V., Periodic Hierarchical Load Balancing for Large Supercomputers. International Journal of High Performance Computing Applications 2011, 25, (4), 371-385.

    • Bhatele, A.; Bohm, E.; Kale, L. V., Optimizing communication for Charm plus plus applications by reducing network contention. Concurrency and Computation-Practice & Experience 2011, 23, (2), 211-222. 

    • Kunzman, D. M.; Kale, L. V., Programming heterogeneous clusters with accelerators using object-based programming. Scientific Programming 2011, 19, (1), 47-62.

  • 2010
    • Bhatele, A.; Wesolowski, L.; Bohm, E.; Solomonik, E.; Kale, L. V., Understanding Application Performance via Micro-benchmarks on Three Large Supercomputers: Intrepid, Ranger and Jaguar. International Journal of High Performance Computing Applications 2010, 24, (4), 411-427. 

  • 2009
    • Dooley, I.; Mangala, S.; Kale, L.; Geubelle, P., Parallel Simulations of Dynamic Fracture Using Extrinsic Cohesive Elements. Journal of Scientific Computing 2009, 39, (1), 144-165.

    • Cappello, F.; Geist, A.; Gropp, B.; Kale, L.; Kramer, B.; Snir, M., Toward Exascale Resilience. International Journal of High Performance Computing Applications 2009, 23, (4), 374-388.

    • Kale, L., Early Application Development/Tuning and Application Characterization/Segmentation. International Journal of High Performance Computing Applications 2009, 23, (4), 411-412.

    • Kale, L., Programming Models at Exascale: Adaptive Runtime Systems, Incomplete Simple Languages, and Interoperability. International Journal of High Performance Computing Applications 2009, 23, (4), 344-346.

  • 2008
    • Mangala, S.; Wilmarth, T.; Chakravorty, S.; Choudhury, N.; Kale, L. V.; Geubelle, P. H., Parallel adaptive simulations of dynamic fracture events. Engineering with Computers 2008, 24, (4), 341-358.

    • Bohm, E.; Bhatele, A.; Kale, L. V.; Tuckerman, M. E.; Kumar, S.; Gunnels, J. A.; Martyna, G. J., Fine-grained parallelization of the Car-Parrinello ab initio molecular dynamics method on the IBM Blue Gene/L supercomputer. IBM Journal of Research and Development 2008, 52, (1-2), 159-175.

    • Kumar, S.; Huang, C.; Zheng, G.; Bohm, E.; Bhatele, A.; Phillips, J. C.; Yu, H.; Kale, L. V., Scalable molecular dynamics with NAMD on the IBM Blue Gene/L system. IBM Journal of Research and Development 2008, 52, (1-2), 177-188.

    • Schulten, K.; Phillips, J. C.; Kale, L. V.; Bhatele, A. Biomolecular modeling in the era of petascale computing, In Petascale Computing: Algorithms and Applications, Bader, D., Ed. Chapman and Hall/CRC Press, Taylor and Francis Group: New York, 2008; pp 165-181.

  • 2006
    • Lawlor, O. S.; Chakravorty, S.; Wilmarth, T. L.; Choudhury, N.; Dooley, I.; Zheng, G. B.; Kale, L. V., ParFUM: a parallel framework for unstructured meshes for scalable dynamic physics applications. Engineering with Computers 2006, 22, (3-4), 215-235.

    • Wang, K.; Chang, A.; Kale, L. V.; Dantzig, J. A., Parallelization of a level set method for simulating dendritic growth. Journal of Parallel and Distributed Computing 2006, 66, (11), 1379-1386.

  • 1999
    • Bhandarkar, M., Budescu, G., Humphrey, W. F., Izaguirre, J. A., Izrailev, S., Kalé, L. V., Kosztin, D., Molnar, F., Phillips, J. C., and Schulten, K. (1999), "BioCoRE: A Collaboratory for Structural Biology," in A. G. Bruzzone, A. Uchrmacher, and E. H. Page, eds., Proceedings of the SCS International Conference on Web-based Modeling and Simulation, San Francisco, CA, pp. 242-251.

  • 1998
    • Kalé, L. V. (1998), "Programming Languages for CSE: The State of the Art," IEEE Computational Science and Engineering, 5/2, pp. 18-26.

    • Kalé, L. V., Bhandarkar, M., Brunner, R., Krawetz, N., Phillips, J., and Shinozaki, A. (1998), "Namd: A Case Study in Multilingual Parallel Programming," Lecture Notes in Computer Science, 1366, pp. 367-381.

    • Kalé, L. V., Bhandarkar, M., Brunner R., and Yelon J. (1998), "Multiparadigm, Multilingual Interoperability: Experience with Converse," Lecture Notes in Computer Science, 1388, pp. 111-112.

  • 1996
    • Kalé, L. V. and Krishnan, S. (1996), "Charm++," in G. V. Wilson and P. Lu, eds., Parallel Programming Using C++ (Cambridge, MA: MIT Press), pp. 179-218.

    • Kalé, L. V., Bhandarkar, M., Jagathesan, N., Krishnan, S. (1996), "Converse: An Interoperable Framework for Parallel Programming," in Proceedings of the 10th International Parallel Processing Symposium, Honolulu, HI, April, pp. 212-217.


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