EAIBench: An Energy Efficiency Benchmark for AI Training
The increase in computing power has prompted more considerable artificial intelligence (AI)
model scales. From 341K multiply-accumulate operations (MACs) of LeNet-5 to 4.11 G …
model scales. From 341K multiply-accumulate operations (MACs) of LeNet-5 to 4.11 G …
Hpc ai500: Representative, repeatable and simple hpc ai benchmarking
Recent years witness a trend of applying large-scale distributed deep learning algorithms
(HPC AI) in both business and scientific computing areas, whose goal is to speed up the …
(HPC AI) in both business and scientific computing areas, whose goal is to speed up the …
A Production Suite for Failure Detectors
Designing a failure detection algorithm, implementing it, and assessing its performance is
extremely complex. The behavior of a failure detector (FD) implementation varies with the …
extremely complex. The behavior of a failure detector (FD) implementation varies with the …
[HTML][HTML] Stars shine: The report of 2021 BenchCouncil awards
T Zhan, S Chen - BenchCouncil Transactions on Benchmarks, Standards …, 2021 - Elsevier
Stars shine: The report of 2021 BenchCouncil awards - ScienceDirect Skip to main contentSkip
to article Elsevier logo Journals & Books Search RegisterSign in View PDF Download full …
to article Elsevier logo Journals & Books Search RegisterSign in View PDF Download full …
3PEIC: Computing Power Evaluation Framework for Distributed Heterogeneous Intelligent Computing Systems
C Han, Z Li, Z Li - 2023 IEEE Smart World Congress (SWC), 2023 - ieeexplore.ieee.org
Computing Power Network (CPN) plays an important role as an infrastructure in various
application fields. The evaluation of computing power in distributed heterogeneous …
application fields. The evaluation of computing power in distributed heterogeneous …
From Investment to Payoff: Exploring the CostImplications of AI Adoption in InventoryManagement Across the Different Phases
L Sheekh Kalil, L Offor-Ugwuka - 2024 - diva-portal.org
Method; These thesis philosophical assumptions are guided by a relativist ontology and
socialconstructionist epistemology. The abductive approach was used where Qualitative …
socialconstructionist epistemology. The abductive approach was used where Qualitative …
DNNEmu: A Lightweight Performance Emulator for Distributed DNN Training
J Wang, E Yu, D Dong, Z Pang - International Conference on Algorithms …, 2022 - Springer
Distributed deep learning system usually leverages large-scale GPU clusters to speed up
training. Therefore, for organizations lacking GPU resources temporarily, it is difficult to …
training. Therefore, for organizations lacking GPU resources temporarily, it is difficult to …
A systematic study on benchmarking AI inference accelerators
AI inference accelerators have drawn extensive attention. But none of the previous work
performs a holistic and systematic benchmarking on AI inference accelerators. First, an end …
performs a holistic and systematic benchmarking on AI inference accelerators. First, an end …