The GAP Benchmark Suite
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Abstract (arXiv)
We present a graph processing benchmark suite with the goal of helping to standardize graph processing evaluations. Fewer differences between graph processing evaluations will make it easier to compare different research efforts and quantify improvements. The benchmark not only specifies graph kernels, input graphs, and evaluation methodologies, but it also provides optimized baseline implementations. These baseline implementations are representative of state-of-the-art performance, and thus new contributions should outperform them to demonstrate an improvement. The input graphs are sized appropriately for shared memory platforms, but any implementation on any platform that conforms to the benchmark's specifications could be compared. This benchmark suite can be used in a variety of settings. Graph framework developers can demonstrate the generality of their programming model by implementing all of the benchmark's kernels and delivering competitive performance on all of the benchmark's graphs. Algorithm designers can use the input graphs and the baseline implementations to demonstrate their contribution. Platform designers and performance analysts can use the suite as a workload representative of graph processing.
Key facts. Cited by 14 papers in the map (data through 7 Oct 2026). First posted on arXiv 14 Aug 2015.
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Citing papers per year: 2021: 1; 2022: 2; 2023: 2; 2024: 5; 2025: 3; 2026: 1.
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- 2024SpecExec: Massively Parallel Speculative Decoding for Interactive LLM Inference on Consumer Devicescited by 45
- 2023TpuGraphs: A Performance Prediction Dataset on Large Tensor Computational Graphscited by 16
- 2024GermanPartiesQA: Benchmarking Commercial Large Language Models and AI Companions for Political Alignment and Sycophancycited by 14
- 2021GraphMineSuite: Enabling High-Performance and Programmable Graph Mining Algorithms with Set Algebracited by 10
- 2022Fine-Grained Address Segmentation for Attention-Based Variable-Degree Prefetchingcited by 5
- 2026ArchAgent: Agentic AI-driven Computer Architecture Discoverycited by 5
- 2023Gender Bias in Transformer Models: A comprehensive surveycited by 2
- 2024PaCKD: Pattern-Clustered Knowledge Distillation for Compressing Memory Access Prediction Modelscited by 2
- 2025Vulcan: Instance-specialized, Verifiable Systems Heuristics Through LLM-driven Searchcited by 1
- 2022Learning to Rank Graph-based Application Objects on Heterogeneous Memoriescited by 0
- 2024Accelerating Computer Architecture Simulation through Machine Learningcited by 0
- 2024A Two Level Neural Approach Combining Off-Chip Prediction with Adaptive Prefetch Filteringcited by 0
- 2026ArchAgent: Agentic AI-driven Computer Architecture Discovery25 Feb 2026
- 2025Vulcan: Instance-specialized, Verifiable Systems Heuristics Through LLM-driven Search31 Dec 2025
- 2025A Comparative Study of OpenMP Scheduling Algorithm Selection Strategies27 Jul 2025
- 2025Learning Semantics, Not Addresses: Runtime Neural Prefetching for Far Memory31 May 2025
- 2024GermanPartiesQA: Benchmarking Commercial Large Language Models and AI Companions for Political Alignment and Sycophancy25 Jul 2024
- 2024SpecExec: Massively Parallel Speculative Decoding for Interactive LLM Inference on Consumer Devices4 Jun 2024
- 2024A Two Level Neural Approach Combining Off-Chip Prediction with Adaptive Prefetch Filtering22 Mar 2024
- 2024Accelerating Computer Architecture Simulation through Machine Learning28 Feb 2024
- 2024PaCKD: Pattern-Clustered Knowledge Distillation for Compressing Memory Access Prediction Models21 Feb 2024
- 2023TpuGraphs: A Performance Prediction Dataset on Large Tensor Computational Graphs25 Aug 2023
- 2023Gender Bias in Transformer Models: A comprehensive survey18 Jun 2023
- 2022Learning to Rank Graph-based Application Objects on Heterogeneous Memories4 Nov 2022
- 2026ArchAgent: Agentic AI-driven Computer Architecture Discovery25 Feb 2026
- 2023TpuGraphs: A Performance Prediction Dataset on Large Tensor Computational Graphscited by 16
- 2024GermanPartiesQA: Benchmarking Commercial Large Language Models and AI Companions for Political Alignment and Sycophancycited by 14
- 2021GraphMineSuite: Enabling High-Performance and Programmable Graph Mining Algorithms with Set Algebracited by 10
- 2022Fine-Grained Address Segmentation for Attention-Based Variable-Degree Prefetchingcited by 5
- 2023Gender Bias in Transformer Models: A comprehensive surveycited by 2
- 2024PaCKD: Pattern-Clustered Knowledge Distillation for Compressing Memory Access Prediction Modelscited by 2
- 2025Vulcan: Instance-specialized, Verifiable Systems Heuristics Through LLM-driven Searchcited by 1
- 2022Learning to Rank Graph-based Application Objects on Heterogeneous Memoriescited by 0
- 2024Accelerating Computer Architecture Simulation through Machine Learningcited by 0
- 2024A Two Level Neural Approach Combining Off-Chip Prediction with Adaptive Prefetch Filteringcited by 0
- 2025Learning Semantics, Not Addresses: Runtime Neural Prefetching for Far Memorycited by 0
- 2025A Comparative Study of OpenMP Scheduling Algorithm Selection Strategiescited by 0
- 2025Vulcan: Instance-specialized, Verifiable Systems Heuristics Through LLM-driven Search31 Dec 2025
- 2025A Comparative Study of OpenMP Scheduling Algorithm Selection Strategies27 Jul 2025
- 2025Learning Semantics, Not Addresses: Runtime Neural Prefetching for Far Memory31 May 2025
- 2024GermanPartiesQA: Benchmarking Commercial Large Language Models and AI Companions for Political Alignment and Sycophancy25 Jul 2024
- 2024A Two Level Neural Approach Combining Off-Chip Prediction with Adaptive Prefetch Filtering22 Mar 2024
- 2024Accelerating Computer Architecture Simulation through Machine Learning28 Feb 2024
- 2024PaCKD: Pattern-Clustered Knowledge Distillation for Compressing Memory Access Prediction Models21 Feb 2024
- 2023TpuGraphs: A Performance Prediction Dataset on Large Tensor Computational Graphs25 Aug 2023
- 2023Gender Bias in Transformer Models: A comprehensive survey18 Jun 2023
- 2022Learning to Rank Graph-based Application Objects on Heterogeneous Memories4 Nov 2022
- 2022Fine-Grained Address Segmentation for Attention-Based Variable-Degree Prefetching1 May 2022
- 2021GraphMineSuite: Enabling High-Performance and Programmable Graph Mining Algorithms with Set Algebra5 Mar 2021