Performance and Power: Systematic Evaluation of AI Workloads on Accelerators with CARAML
Fuente:
arXiv
Guardado en:
| Autores principales: | John, Chelsea Maria, Nassyr, Stepan, Penke, Carolin, Herten, Andreas |
|---|---|
| Formato: | Preprint |
| Publicado: |
2024
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
Characterizing and Optimizing LLM Inference Workloads on CPU-GPU Coupled Architectures
por: Vellaisamy, Prabhu, et al.
Publicado: (2025)
por: Vellaisamy, Prabhu, et al.
Publicado: (2025)
SCAR: Scheduling Multi-Model AI Workloads on Heterogeneous Multi-Chiplet Module Accelerators
por: Odema, Mohanad, et al.
Publicado: (2024)
por: Odema, Mohanad, et al.
Publicado: (2024)
RedFuser: An Automatic Operator Fusion Framework for Cascaded Reductions on AI Accelerators
por: Tang, Xinsheng, et al.
Publicado: (2026)
por: Tang, Xinsheng, et al.
Publicado: (2026)
Profiling Concurrent Vision Inference Workloads on NVIDIA Jetson -- Extended
por: Chakraborty, Abhinaba, et al.
Publicado: (2025)
por: Chakraborty, Abhinaba, et al.
Publicado: (2025)
Cloud to Edge: Benchmarking LLM Inference On Hardware-Accelerated Single-Board Computers
por: Renney, Harri, et al.
Publicado: (2026)
por: Renney, Harri, et al.
Publicado: (2026)
Revisiting Disaggregated Large Language Model Serving for Performance and Energy Implications
por: Li, Jiaxi, et al.
Publicado: (2025)
por: Li, Jiaxi, et al.
Publicado: (2025)
Performance Implications of Multi-Chiplet Neural Processing Units on Autonomous Driving Perception
por: Odema, Mohanad, et al.
Publicado: (2024)
por: Odema, Mohanad, et al.
Publicado: (2024)
GPT-OSS-20B: A Comprehensive Deployment-Centric Analysis of OpenAI's Open-Weight Mixture of Experts Model
por: Kumar, Deepak, et al.
Publicado: (2025)
por: Kumar, Deepak, et al.
Publicado: (2025)
Systematic Characterization of LLM Quantization: A Performance, Energy, and Quality Perspective
por: Shi, Tianyao, et al.
Publicado: (2025)
por: Shi, Tianyao, et al.
Publicado: (2025)
DABench-LLM: Standardized and In-Depth Benchmarking of Post-Moore Dataflow AI Accelerators for LLMs
por: Hu, Ziyu, et al.
Publicado: (2025)
por: Hu, Ziyu, et al.
Publicado: (2025)
ARKV: Adaptive and Resource-Efficient KV Cache Management under Limited Memory Budget for Long-Context Inference in LLMs
por: Lei, Jianlong, et al.
Publicado: (2026)
por: Lei, Jianlong, et al.
Publicado: (2026)
COMET: Neural Cost Model Explanation Framework
por: Chaudhary, Isha, et al.
Publicado: (2023)
por: Chaudhary, Isha, et al.
Publicado: (2023)
Exploring and Evaluating Real-world CXL: Use Cases and System Adoption
por: Wang, Xi, et al.
Publicado: (2024)
por: Wang, Xi, et al.
Publicado: (2024)
Performance Analysis of HPC applications on the Aurora Supercomputer: Exploring the Impact of HBM-Enabled Intel Xeon Max CPUs
por: Ibeid, Huda, et al.
Publicado: (2025)
por: Ibeid, Huda, et al.
Publicado: (2025)
The Energy Blind Spot: NVIDIA's Flagship Edge AI Hardware Cannot Support Process-Level Energy Attribution
por: Panigrahy, Deepak, et al.
Publicado: (2026)
por: Panigrahy, Deepak, et al.
Publicado: (2026)
Evaluating the Potential of In-Memory Processing to Accelerate Homomorphic Encryption
por: Mwaisela, Mpoki, et al.
Publicado: (2024)
por: Mwaisela, Mpoki, et al.
Publicado: (2024)
GigaAPI for GPU Parallelization
por: Suvarna, M., et al.
Publicado: (2025)
por: Suvarna, M., et al.
Publicado: (2025)
UPMEM Unleashed: Software Secrets for Speed
por: Chmielewski, Krystian, et al.
Publicado: (2025)
por: Chmielewski, Krystian, et al.
Publicado: (2025)
Dissecting the NVIDIA Hopper Architecture through Microbenchmarking and Multiple Level Analysis
por: Luo, Weile, et al.
Publicado: (2025)
por: Luo, Weile, et al.
Publicado: (2025)
Experimental Assessment of Containers Running on Top of Virtual Machines
por: Aqasizade, Hossein, et al.
Publicado: (2024)
por: Aqasizade, Hossein, et al.
Publicado: (2024)
Compiler Support for Speculation in Decoupled Access/Execute Architectures
por: Szafarczyk, Robert, et al.
Publicado: (2025)
por: Szafarczyk, Robert, et al.
Publicado: (2025)
Parallelizing a modern GPU simulator
por: Huerta, Rodrigo, et al.
Publicado: (2025)
por: Huerta, Rodrigo, et al.
Publicado: (2025)
Can Asymmetric Tile Buffering Be Beneficial?
por: Wang, Chengyue, et al.
Publicado: (2025)
por: Wang, Chengyue, et al.
Publicado: (2025)
Exploiting long vectors with a CFD code: a co-design show case
por: Blancafort, Marc, et al.
Publicado: (2024)
por: Blancafort, Marc, et al.
Publicado: (2024)
Fusing Depthwise and Pointwise Convolutions for Efficient Inference on GPUs
por: Qararyah, Fareed, et al.
Publicado: (2024)
por: Qararyah, Fareed, et al.
Publicado: (2024)
Simopt -- Simulation pass for Speculative Optimisation of FPGA-CAD flow
por: Wadhwa, Eashan, et al.
Publicado: (2024)
por: Wadhwa, Eashan, et al.
Publicado: (2024)
Scaling Intelligence: Designing Data Centers for Next-Gen Language Models
por: Tithi, Jesmin Jahan, et al.
Publicado: (2025)
por: Tithi, Jesmin Jahan, et al.
Publicado: (2025)
Flex-TPU: A Flexible TPU with Runtime Reconfigurable Dataflow Architecture
por: Elbtity, Mohammed, et al.
Publicado: (2024)
por: Elbtity, Mohammed, et al.
Publicado: (2024)
Power Stabilization for AI Training Datacenters
por: Choukse, Esha, et al.
Publicado: (2025)
por: Choukse, Esha, et al.
Publicado: (2025)
Efficient Edge AI: Deploying Convolutional Neural Networks on FPGA with the Gemmini Accelerator
por: Peccia, Federico Nicolas, et al.
Publicado: (2024)
por: Peccia, Federico Nicolas, et al.
Publicado: (2024)
Heterogeneous Computing: The Key to Powering the Future of AI Agent Inference
por: Zhao, Yiren, et al.
Publicado: (2026)
por: Zhao, Yiren, et al.
Publicado: (2026)
Sustainable Supercomputing for AI: GPU Power Capping at HPC Scale
por: Zhao, Dan, et al.
Publicado: (2024)
por: Zhao, Dan, et al.
Publicado: (2024)
Improving AI Efficiency in Data Centres by Power Dynamic Response
por: Marinoni, Andrea, et al.
Publicado: (2025)
por: Marinoni, Andrea, et al.
Publicado: (2025)
Efficient Hardware Accelerator Based on Medium Granularity Dataflow for SpTRSV
por: Chen, Qian, et al.
Publicado: (2024)
por: Chen, Qian, et al.
Publicado: (2024)
Evaluating Emerging AI/ML Accelerators: IPU, RDU, and NVIDIA/AMD GPUs
por: Peng, Hongwu, et al.
Publicado: (2023)
por: Peng, Hongwu, et al.
Publicado: (2023)
Design and Implementation of an IoT Cluster with Raspberry Pi Powered by Solar Energy: A Theoretical Approach
por: Portillo, Noel
Publicado: (2025)
por: Portillo, Noel
Publicado: (2025)
ZKProphet: Understanding Performance of Zero-Knowledge Proofs on GPUs
por: Verma, Tarunesh, et al.
Publicado: (2025)
por: Verma, Tarunesh, et al.
Publicado: (2025)
Vector-Centric Machine Learning Systems: A Cross-Stack Approach
por: Jiang, Wenqi
Publicado: (2025)
por: Jiang, Wenqi
Publicado: (2025)
Workload-Aware Hardware Accelerator Mining for Distributed Deep Learning Training
por: Adnan, Muhammad, et al.
Publicado: (2024)
por: Adnan, Muhammad, et al.
Publicado: (2024)
The DMA Streaming Framework: Kernel-Level Buffer Orchestration for High-Performance AI Data Paths
por: Graziano, Marco
Publicado: (2026)
por: Graziano, Marco
Publicado: (2026)
Ejemplares similares
-
Characterizing and Optimizing LLM Inference Workloads on CPU-GPU Coupled Architectures
por: Vellaisamy, Prabhu, et al.
Publicado: (2025) -
SCAR: Scheduling Multi-Model AI Workloads on Heterogeneous Multi-Chiplet Module Accelerators
por: Odema, Mohanad, et al.
Publicado: (2024) -
RedFuser: An Automatic Operator Fusion Framework for Cascaded Reductions on AI Accelerators
por: Tang, Xinsheng, et al.
Publicado: (2026) -
Profiling Concurrent Vision Inference Workloads on NVIDIA Jetson -- Extended
por: Chakraborty, Abhinaba, et al.
Publicado: (2025) -
Cloud to Edge: Benchmarking LLM Inference On Hardware-Accelerated Single-Board Computers
por: Renney, Harri, et al.
Publicado: (2026)