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Precise event sampling, a profiling feature in commodity processors, accurately pinpoints instructions triggering hardware events. While widely utilized, support from vendors varies, impacting accuracy, stability, overhead, and functionality. Our study benchmarks Intel PEBS and AMD IBS, revealing PEBS's finer-grained accuracy and IBS's richer information but lower stability. PEBS incurs lower time overhead, while IBS suffers from accuracy issues. OS signal delivery adds significant time overhead. Both PEBS and IBS exhibit sampling bias. Our findings hold in a full-fledged profiling tool on modern Intel and AMD machines. This comparison offers valuable insights for hardware designers and profiling tool developers. <a href="https://github.com/ParCoreLab/PES-artifact" class="text-xl font-semibold font-serif visited:text-teal-700">All the artifacts and benchmarks can be found.</a>
<div class="card"> Ilyas Turimbetov, MA Sasongko, and Didem Unat, <a href="https://dl.acm.org/doi/pdf/10.1145/3642961#page=8">GPU-Initiated Resource Allocation for Irregular Workloads</a>, International Workshop on Extreme Heterogeneity Solutions (ExHET), 2024 </div>
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<div class="card"> I Ismayilov, J Baydamirli, D Sagbili, M Wahib, D Unat, <a href="https://dl.acm.org/doi/abs/10.1145/3577193.3593713">Multi-GPU Communication Schemes for Iterative Solvers: When CPUs are Not in Charge</a>, ICS ’23: Proceedings of the 37th International Conference on Supercomputing, 192–202. </div>
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<div class="card"> MA Sasongko, M Chabbi, PHJ Kelly, D Unat, <a href="https://scholar.google.com/citations?view_op=view_citation&hl=en&user=NR70RpYAAAAJ&sortby=pubdate&citation_for_view=NR70RpYAAAAJ:35N4QoGY0k4C">Precise Event Sampling on AMD vs Intel: Quantitative and Qualitative Comparison</a>, IEEE Transactions on Parallel and Distributed Systems, vol. 34, no. 5, pp. 1594-1608, May 2023, doi: 10.1109/TPDS.2023.3257105. </div>
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<div class="card"> Issa, M., Sasongko, M., Turimbetov, I., Baydamirli, J., Sağbili, D., Unat, D. (2024). <a href="https://doi.org/10.1145/3650200.3656597">Snoopie: A Multi-GPU Communication Profiler and Visualizer</a>. In Proceedings of the 38th International Conference on Supercomputing. </div>
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<divclass="card"> Ilyas Turimbetov, MA Sasongko, and Didem Unat, <ahref="https://dl.acm.org/doi/10.1145/3642961.3643799">GPU-Initiated Resource Allocation for Irregular Workloads</a>, International Workshop on Extreme Heterogeneity Solutions (ExHET), 2024 </div>
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<div class="card"> I Ismayilov, J Baydamirli, D Sagbili, M Wahib, D Unat, <a href="https://dl.acm.org/doi/abs/10.1145/3577193.3593713">Multi-GPU Communication Schemes for Iterative Solvers: When CPUs are Not in Charge</a>, ICS ’23: Proceedings of the 37th International Conference on Supercomputing, 192–202. </div>
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<div class="card"> MA Sasongko, M Chabbi, PHJ Kelly, D Unat, <a href="https://ieeexplore.ieee.org/document/10068807">Precise Event Sampling on AMD vs Intel: Quantitative and Qualitative Comparison</a>, IEEE Transactions on Parallel and Distributed Systems, vol. 34, no. 5, pp. 1594-1608, May 2023, doi: 10.1109/TPDS.2023.3257105.
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