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- research-articleJune 2024
Input Range Generation for Compiler-Induced Numerical Inconsistencies
ICS '24: Proceedings of the 38th ACM International Conference on SupercomputingMay 2024, Pages 201–212https://doi.org/10.1145/3650200.3656618Compiler-induced numerical inconsistencies present a significant challenge when testing and verifying numerical software—they can arise in a variety of situations, such as when porting code to a new platform or when using a different compiler or ...
- research-articleJune 2024
Shared Virtual Memory: Its Design and Performance Implications for Diverse Applications
ICS '24: Proceedings of the 38th ACM International Conference on SupercomputingMay 2024, Pages 26–37https://doi.org/10.1145/3650200.3656608Discrete GPU accelerators, while providing massive computing power for supercomputers and data centers, have their separate memory domain. Explicit memory management across device and host domains in programming is tedious and error-prone. To improve ...
- research-articleJune 2023
Performance Embeddings: A Similarity-Based Transfer Tuning Approach to Performance Optimization
ICS '23: Proceedings of the 37th ACM International Conference on SupercomputingJune 2023, Pages 50–62https://doi.org/10.1145/3577193.3593714Performance optimization is an increasingly challenging but often repetitive task. While each platform has its quirks, the underlying code transformations rely on data movement and computational characteristics that recur across applications. This paper ...
- research-articleJune 2021
Inter-loop optimization in RAJA using loop chains
ICS '21: Proceedings of the 35th ACM International Conference on SupercomputingJune 2021, Pages 1–12https://doi.org/10.1145/3447818.3461665Typical parallelization approaches such as OpenMP and CUDA provide constructs for parallelizing and blocking for data locality for individual loops. By focusing on each loop separately, these approaches fail to leverage sources of data locality possible ...
- research-articleJune 2021
Does it matter?: OMPSanitizer: an impact analyzer of reported data races in OpenMP programs
ICS '21: Proceedings of the 35th ACM International Conference on SupercomputingJune 2021, Pages 40–51https://doi.org/10.1145/3447818.3460379Data races are a primary source of concurrency bugs in parallel programs. Yet, debugging data races is not easy, even with a large amount of data race detection tools. In particular, there still exists a manually-intensive and time-consuming ...
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- research-articleJune 2021
MD-HM: memoization-based molecular dynamics simulations on big memory system
ICS '21: Proceedings of the 35th ACM International Conference on SupercomputingJune 2021, Pages 215–226https://doi.org/10.1145/3447818.3460365Molecular dynamics (MD) simulation is a fundamental method for modeling ensembles of particles. In this paper, we introduce a new method to improve the performance of MD by leveraging the emerging TB-scale big memory system. In particular, we trade ...
- research-articleJune 2021
Distributed merge forest: a new fast and scalable approach for topological analysis at scale
ICS '21: Proceedings of the 35th ACM International Conference on SupercomputingJune 2021, Pages 367–377https://doi.org/10.1145/3447818.3460358Topological analysis is used in several domains to identify and characterize important features in scientific data, and is now one of the established classes of techniques of proven practical use in scientific computing. The growth in parallelism and ...
- research-articleJune 2021
Optimizing large-scale plasma simulations on persistent memory-based heterogeneous memory with effective data placement across memory hierarchy
ICS '21: Proceedings of the 35th ACM International Conference on SupercomputingJune 2021, Pages 203–214https://doi.org/10.1145/3447818.3460356Particle simulations of plasma are important for understanding plasma dynamics in space weather and fusion devices. However, production simulations that use billions and even trillions of computational particles require high memory capacity. In this work,...
- research-articleJune 2020
AutoParBench: a unified test framework for OpenMP-based parallelizers
ICS '20: Proceedings of the 34th ACM International Conference on SupercomputingJune 2020, Article No.: 28, Pages 1–10https://doi.org/10.1145/3392717.3392744This paper describes AutoParBench, a framework to test OpenMP-based automatic parallelization tools. The core idea of this framework is a common representation, called a "JSON snapshot", that normalizes the output produced by auto-parallelizers. By ...
- research-articleJune 2020
CodeSeer: input-dependent code variants selection via machine learning
ICS '20: Proceedings of the 34th ACM International Conference on SupercomputingJune 2020, Article No.: 43, Pages 1–11https://doi.org/10.1145/3392717.3392741In high performance computing (HPC), scientific simulation codes are executed repeatedly with different inputs. The peak performance of these programs heavily depends on various compiler optimizations, which are often selected agnostically on program ...
- research-articleJune 2020
End-to-end performance modeling of distributed GPU applications
ICS '20: Proceedings of the 34th ACM International Conference on SupercomputingJune 2020, Article No.: 30, Pages 1–12https://doi.org/10.1145/3392717.3392737With the growing number of GPU-based supercomputing platforms and GPU-enabled applications, the ability to accurately model the performance of such applications is becoming increasingly important. Most current performance models for GPU-enabled ...
- research-articleJune 2019
Optimizing computation-communication overlap in asynchronous task-based programs
- Emilio Castillo,
- Nikhil Jain,
- Marc Casas,
- Miquel Moreto,
- Martin Schulz,
- Ramon Beivide,
- Mateo Valero,
- Abhinav Bhatele
ICS '19: Proceedings of the ACM International Conference on SupercomputingJune 2019, Pages 380–391https://doi.org/10.1145/3330345.3330379Asynchronous task-based programming models are gaining popularity to address the programmability and performance challenges in high performance computing. One of the main attractions of these models and runtimes is their potential to automatically ...
- research-articleJune 2019
Power efficient job scheduling by predicting the impact of processor manufacturing variability
ICS '19: Proceedings of the ACM International Conference on SupercomputingJune 2019, Pages 296–307https://doi.org/10.1145/3330345.3330372Modern CPUs suffer from performance and power consumption variability due to the manufacturing process. As a result, systems that do not consider such variability caused by manufacturing issues lead to performance degradations and wasted power. In order ...
- research-articleJune 2019
AMPT-GA: automatic mixed precision floating point tuning for GPU applications
ICS '19: Proceedings of the ACM International Conference on SupercomputingJune 2019, Pages 160–170https://doi.org/10.1145/3330345.3330360Mixed precision computations improve high performance computing throughput for applications that can tolerate decreased mathematical precision in their computations. Native mixed precision computation is commonplace in today's GPGPU accelerators where ...
- research-articleJune 2019
MCEM: Multi-Level Cooperative Exception Model for HPC Workflows
ROSS '19: Proceedings of the 9th International Workshop on Runtime and Operating Systems for SupercomputersJune 2019, Pages 27–32https://doi.org/10.1145/3322789.3328745As fault recovery mechanisms become increasingly important in HPC systems, the need for a new recovery model for workflows on these systems grows as well. While the traditional approach in which each system component attempts its own independent ...
- research-articleJune 2018
Direct-FUSE: Removing the Middleman for High-Performance FUSE File System Support
ROSS'18: Proceedings of the 8th International Workshop on Runtime and Operating Systems for SupercomputersJune 2018, Article No.: 6, Pages 1–8https://doi.org/10.1145/3217189.3217195Developing a file system is a challenging task, especially a kernel-level file system. User-level file systems alleviate the burden and development complexity associated with kernel-level implementations. The Filesystem in Userspace (FUSE) is a widely ...
- research-articleJune 2018
Bootstrapping Parameter Space Exploration for Fast Tuning
- Jayaraman J. Thiagarajan,
- Nikhil Jain,
- Rushil Anirudh,
- Alfredo Gimenez,
- Rahul Sridhar,
- Aniruddha Marathe,
- Tao Wang,
- Murali Emani,
- Abhinav Bhatele,
- Todd Gamblin
ICS '18: Proceedings of the 2018 International Conference on SupercomputingJune 2018, Pages 385–395https://doi.org/10.1145/3205289.3205321The task of tuning parameters for optimizing performance or other metrics of interest such as energy, variability, etc. can be resource and time consuming. Presence of a large parameter space makes a comprehensive exploration infeasible. In this paper, ...
- research-articleJune 2017
Automatic topology mapping of diverse large-scale parallel applications
ICS '17: Proceedings of the International Conference on SupercomputingJune 2017, Article No.: 17, Pages 1–10https://doi.org/10.1145/3079079.3079104Topology-aware mapping aims at assigning tasks to processors in a way that minimizes network load, thus reducing the time spent waiting for communication to complete. Many mapping schemes and algorithms have been proposed. Some are application or domain ...
- research-articleJune 2016
Runtime-Guided Mitigation of Manufacturing Variability in Power-Constrained Multi-Socket NUMA Nodes
ICS '16: Proceedings of the 2016 International Conference on SupercomputingJune 2016, Article No.: 5, Pages 1–12https://doi.org/10.1145/2925426.2926279Current large scale systems show increasing power demands, to the point that it has become a huge strain on facilities and budgets. Researchers in academia, labs and industry are focusing on dealing with this "power wall", striving to find a balance ...
- research-articleJune 2015
Application Runtime Variability and Power Optimization for Exascale Computers
ROSS '15: Proceedings of the 5th International Workshop on Runtime and Operating Systems for SupercomputersJune 2015, Article No.: 3, Pages 1–8https://doi.org/10.1145/2768405.2768408Exascale computing will be as much about solving problems with the least power/energy as about solving them quickly. In the future, systems are likely to be over-provisioned with processors and will rely on hardware-enforced power bounds to allow ...