Abstract
Software engineers now face the difficult task of refactoring serial programs for parallel execution on multicore processors. Currently, they are offered little guidance as to how much benefit may come from this task, or how close they are to the best possible parallelization. This paper presents Kismet, a tool that creates parallel speedup estimates for unparallelized serial programs. Kismet differs from previous approaches in that it does not require any manual analysis or modification of the program. This difference allows quick analysis of many programs, avoiding wasted engineering effort on those that are fundamentally limited. To accomplish this task, Kismet builds upon the hierarchical critical path analysis (HCPA) technique, a recently developed dynamic analysis that localizes parallelism to each of the potentially nested regions in the target program. It then uses a parallel execution time model to compute an approximate upper bound for performance, modeling constraints that stem from both hardware parameters and internal program structure.
Our evaluation applies Kismet to eight high-parallelism NAS Parallel Benchmarks running on a 32-core AMD multicore system, five low-parallelism SpecInt benchmarks, and six medium-parallelism benchmarks running on the finegrained MIT Raw processor. The results are compelling. Kismet is able to significantly improve the accuracy of parallel speedup estimates relative to prior work based on critical path analysis.
- Intel Parallel Advisor 2011. http://software.intel.com/en-us/articles/intel-parallel-advisor.Google Scholar
- NAS Parallel Benchmarks 2.3; OpenMP C. www.hpcc.jp/Omni/.Google Scholar
- V. Adve, J. Mellor-Crummey, M. Anderson, J.-C. Wang, D. A. Reed, and K. Kennedy. An integrated compilation and performance analysis environment for data parallel programs. In SC '95: Proceedings of the ACM/IEEE conference on Supercomputing, 1995. Google Scholar
Digital Library
- A. Agarwal, S. Amarasinghe, R. Barua, M. Frank, W. Lee, V. Sarkar, D. Srikrishna, and M. Taylor. The RAW compiler project. In Proceedings of the Second SUIF Compiler Workshop, 1997.Google Scholar
- G. Ammons, T. Ball, and J. R. Larus. Exploiting hardware performance counters with flow and context sensitive profiling. In PLDI '97: Proceedings of the ACM SIGPLAN Conference on Programming Language Design and Implementation, 1997. Google Scholar
Digital Library
- T. E. Anderson, and E. D. Lazowska. Quartz: A tool for tuning parallel program performance. In SIGMETRICS, vol. 18, 1990. Google Scholar
Digital Library
- T. Austin, and G. S. Sohi. Dynamic dependency analysis of ordinary programs. In ISCA '92: Proceedings of the International Symposium on Computer Architecture, 1992. Google Scholar
Digital Library
- J. Babb, M. Frank, V. Lee, E. Waingold, R. Barua, M. Taylor, J. Kim, S. Devabhaktuni, and A. Agarwal. The raw benchmark suite: computation structures for general purpose computing. In FCCM '97: Proceedings of the IEEE Symposium on FPGA-Based Custom Computing Machines, 1997. Google Scholar
Digital Library
- Bailey et al. The NAS parallel benchmarks. In SC '91: Proceedings of the Conference on Supercomputing, 1991. Google Scholar
Digital Library
- B. J. Barnes, B. Rountree, D. K. Lowenthal, J. Reeves, B. de Supinski, and M. Schulz. A regression-based approach to scalability prediction. In ICS '08: Proceedings of the International Conference on Supercomputing, 2008. Google Scholar
Digital Library
- J. M. Bull, and D. O'Neill. A microbenchmark suite for OpenMP 2.0. SIGARCH Computer Architecture News, Dec 2001. Google Scholar
Digital Library
- E. S. Chung, P. A. Milder, J. C. Hoe, and K. Mai. Single-chip heterogeneous computing: Does the future include custom logic, fpgas, and gpgpus? In MICRO '10: Proceedings of the IEEE/ACM International Symposium on Microarchitecture, 2010. Google Scholar
Digital Library
- L. De Rose, and D. Reed. Svpablo: A multi-language architecture-independent performance analysis system. In ICPP '99:International Conference on Parallel Processing, 1999. Google Scholar
Digital Library
- E. Waingold et al. Baring It All to Software: Raw Machines. IEEE Computer, Sept 1997. Google Scholar
Digital Library
- S. Garcia, D. Jeon, C. Louie, S. Kota Venkata, and M. B. Taylor. Bridging the parallelization gap: Automating parallelism discovery and planning. In HotPar '10: Proceedings of the USENIX workshop on Hot Topics in Parallelism, 2010.Google Scholar
- S. Garcia, D. Jeon, C. Louie, and M. B. Taylor. Kremlin: Rethinking and rebooting gprof for the multicore age. In PLDI '11: Proceedings of the Conference on Programming Language Design and Implementation, 2011. Google Scholar
Digital Library
- N. Goulding, J. Sampson, G. Venkatesh, S. Garcia, J. Auricchio, J. Babb, M. Taylor, and S. Swanson. GreenDroid: A Mobile Application Processor for a Future of Dark Silicon. In Hotchips, 2010.Google Scholar
Cross Ref
- Y. He, C. Leiserson, and W. Leiserson. The Cilkview Scalability Analyzer. In SPAA '10: Proceedings of the Symposium on Parallelism in Algorithms and Architectures, 2010. Google Scholar
Digital Library
- M. D. Hill, and M. R. Marty. Amdahl's law in the multicore era. IEEE Computer, July 2008. Google Scholar
Digital Library
- K. Hoste, A. Phansalkar, L. Eeckhout, A. Georges, L. K. John, and K. De Bosschere. Performance prediction based on inherent program similarity. In PACT '06: Parallel Architectures and Compilation Techniques, 2006. Google Scholar
Digital Library
- D. Jeon, S. Garcia, C. Louie, S. Kota Venkata, and M. B. Taylor. Kremlin: Like gprof, but for Parallelization. In PPoPP '11: Principles and Practice of Parallel Programming, 2011. Google Scholar
Digital Library
- D. Jeon, S. Garcia, C. Louie, and M. B. Taylor. Parkour: Parallel speedup estimates for serial programs. In HotPar '11: Proceedings of the USENIX workshop on Hot Topics in Parallelism, May 2011. Google Scholar
Digital Library
- T. S. Karkhanis, and J. E. Smith. A first-order superscalar processor model. In ISCA '04: Proceedings of the International Symposium on Computer Architecture. Google Scholar
Digital Library
- H. Kim, A. Raman, F. Liu, J. W. Lee, and D. I. August. Scalable speculative parallelization on commodity clusters. In MICRO '10: Proceedings of the IEEE/ACM International Symposium on Microarchitecture, 2010. Google Scholar
Digital Library
- M. Kim, H. Kim, and C. Luk. Prospector: A dynamic data-dependence profiler to help parallel programming. In HotPar '10: Proceedings of the USENIX workshop on Hot Topics in parallelism, 2010.Google Scholar
- M. Kim, H. Kim, and C.-K. Luk. SD3: A scalable approach to dynamic data-dependence profiling. MICRO '10: Proceedings of the International Symposium on Microarchitecture, 2010. Google Scholar
Digital Library
- M. Kulkarni, M. Burtscher, R. Inkulu, K. Pingali, and C. Casçaval. How much parallelism is there in irregular applications? In PPoPP '09: Proceedings of the ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, 2009. Google Scholar
Digital Library
- M. Kumar. Measuring parallelism in computation-intensive scientific/engineering applications. IEEE TOC, Sep 1988. Google Scholar
Digital Library
- M. S. Lam, and R. P. Wilson. Limits of control flow on parallelism. In ISCA, 1992. Google Scholar
Digital Library
- J. R. Larus. Loop-level parallelism in numeric and symbolic programs. IEEE Trans. Parallel Distrib. Syst., 1993. Google Scholar
Digital Library
- C. Lattner, and V. Adve. LLVM: A compilation framework for lifelong program analysis & transformation. In CGO '04: Proceedings of the International Symposium on Code Generation and Optimization, 2004. Google Scholar
Digital Library
- W. Lee, R. Barua, M. Frank, D. Srikrishna, J. Babb, V. Sarkar, and S. Amarasinghe. Space-time scheduling of instruction-level parallelism on a Raw machine. In ASPLOS '98: International Conference on Architectural Support for Programming Languages and Operating Systems, Oct 1998. Google Scholar
Digital Library
- S.-W. Liao, A. Diwan, R. P. Bosch, Jr., A. Ghuloum, and M. S. Lam. SUIF Explorer: an interactive and interprocedural parallelizer. In PPoPP '99: Proceedings of the ACM SIGPLAN symposium on Principles and Practice of Parallel Programming. Google Scholar
Digital Library
- G. Loh. A time-stamping algorithm for efficient performance estimation of superscalar processors. In SIGMETRICS, 2001. Google Scholar
Digital Library
- M. B. Taylor et al. Evaluation of the raw microprocessor: An exposed-wire-delay architecture for ilp and streams. In ISCA '04: Proceedings of the International Symposium on Computer Architecture, Jun 2004. Google Scholar
Digital Library
- M. B. Taylor et al. The Raw Microprocessor: A Computation Fabric for Software Circuits and General-Purpose Programs. In IEEE Micro, Mar/Apr 2002. Google Scholar
Digital Library
- M. Martin, D. Sorin, B. Beckmann, M. Marty, M. Xu, A. R. Alameldeen, K. Moore, M. Hill, and D. Wood. Multifacet's general execution-driven multiprocessor simulator (GEMS) toolset. SIGARCH Comput. Archit. News, Nov 2005. Google Scholar
Digital Library
- M. Martonosi, D. Felt, and M. Heinrich. Integrating performance monitoring and communication in parallel computers. In SIGMETRICS, 1996. Google Scholar
Digital Library
- B. P. Miller, M. D. Callaghan, J. M. Cargille, J. K. Hollingsworth, R. B. Irvin, K. L. Karavanic, K. Kunchithapadam, and T. Newhall. The Paradyn Parallel Performance Measurement Tool. IEEE Computer, 1995. Google Scholar
Digital Library
- N. Nethercote, and J. Seward. How to shadow every byte of memory used by a program. In VEE '07: Proceedings of the 3rd international conference on Virtual Execution Environments, 2007. Google Scholar
Digital Library
- N. Nethercote, and J. Seward. Valgrind: A framework for heavyweight dynamic binary instrumentation. In PLDI '07: Proceedings of the Conference on Programming Language Design and Implementation, 2007. Google Scholar
Digital Library
- D. Ofelt, and J. L. Hennessy. Efficient performance prediction for modern microprocessors. In SIGMETRICS, 2000. Google Scholar
Digital Library
- M. K. Prabhu, and K. Olukotun. Exposing speculative thread parallelism in spec2000. In PPoPP '05: Proceedings of the ACM SIGPLAN symposium on Principles and Practice of Parallel Programming, 2005. Google Scholar
Digital Library
- E. Raman, G. Ottoni, A. Raman, M. J. Bridges, and D. I. August. Parallel-stage decoupled software pipelining. In CGO '08: Proceedings of the International Symposium on Code Generation and Optimization, 2008. Google Scholar
Digital Library
- L. Rauchwerger, P. K. Dubey, and R. Nair. Measuring limits of parallelism and characterizing its vulnerability to resource constraints. In MICRO '93: Proceedings of the international symposium on Microarchitecture, 1993. Google Scholar
Digital Library
- S. Bell et al. TILE64 - Processor: A 64-Core SoC with Mesh Interconnect. In ISSCC '08: IEEE Solid-State Circuits Conference, 2008.Google Scholar
- N. R. Tallent, and J. M. Mellor Crummey. Effective performance measurement and analysis of multithreaded applications. In PPoPP '09: Proceedings of the ACM SIGPLAN symposium on Principles and practice of parallel programming, 2009. Google Scholar
Digital Library
- M. B. Taylor. Design Decisions in the Implementation of a Raw Architecture Workstation. Master's thesis, Massachusetts Institute of Technology, Sept 1999.Google Scholar
- M. B. Taylor. Tiled Microprocessors. Ph.D. thesis, Massachusetts Institute of Technology, 2007. Google Scholar
Digital Library
- M. B. Taylor, W. Lee, S. P. Amarasinghe, and A. Agarwal. Scalar operand networks. IEEE Transactions on Parallel and Distributed Systems, Feb 2005. Google Scholar
Digital Library
- K. B. Theobald, G. R. Gao, and L. J. Hendren. On the limits of program parallelism and its smoothability. In MICRO '92: Proceedings of the International Symposium on Microarchitecture, 1992. Google Scholar
Digital Library
- D. W. Wall. Limits of instruction-level parallelism. In Proceedings of the Conference on Architectural Support for Programming Languages and Operating Systems, 1991. Google Scholar
Digital Library
- J. Zhai, W. Chen, and W. Zheng. Phantom: predicting performance of parallel applications on large-scale parallel machines using a single node. In PPoPP '10: Proceedings of the ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, 2010. Google Scholar
Digital Library
- X. Zhang, A. Navabi, and S. Jagannathan. Alchemist: A transparent dependence distance profiling infrastructure. In CGO '09: Proceedings of the International Symposium on Code Generation and Optimization, 2009. Google Scholar
Digital Library
- Y. Zhang, and R. Gupta. Timestamped whole program path representation and its applications. In PLDI '01: Proceedings of the ACM SIGPLAN Conference on Programming Language Design and Implementation, 2001. Google Scholar
Digital Library
- L. Zhao, R. Iyer, J. Moses, R. lllikkal, S. Makineni, and D. Newell. Exploring Large-Scale CMP Architectures Using ManySim. IEEE Micro, July 2007. Google Scholar
Digital Library
- Q. Zhao, D. Bruening, and S. Amarasinghe. Efficient memory shadowing for 64-bit architectures. In ISMM '10: Proceedings of the International Symposium on Memory Management, Jun 2010. Google Scholar
Digital Library
- Q. Zhao, D. Bruening, and S. Amarasinghe. Umbra: Efficient and scalable memory shadowing. In CGO '10: Proceedings of the IEEE/ACM international symposium on Code Generation and Optimization, 2010. Google Scholar
Digital Library
- H. Zhong, M. Mehrara, S. Lieberman, and S. Mahlke. Uncovering hidden loop level parallelism in sequential applications. In HPCA '08: Proceedings of the International Symposium on High Performance Computer Architecture, 2008.Google Scholar
- D. A. Zier, and B. Lee. Performance evaluation of dynamic speculative multithreading with the cascadia architecture. IEEE Transactions on Parallel and Distributed Systems, Jan 2010. Google Scholar
Digital Library
Index Terms
Kismet: parallel speedup estimates for serial programs
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