SlideServe
Télécharger Obtenir Pro
Menu
Accueil Pro
Préférences
ApparenceLight Aide et commentaires
© SlideServe · v2026

System Simulation Of 1000-cores Heterogeneous SoCs

oleg avatar
oleg
21 diapositives · 337 Views · Jul 27, 2014

This paper presents SIMinG-1k, a GPU-accelerated simulator designed for efficient simulation of 1000-core heterogeneous System-on-Chips (SoCs). Aimed at addressing the urgent need for accurate thermal and power evaluations, SIMinG-1k enhances performance for data-intensive workloads, including financial simulations and medical imaging. The framework achieves high scalability and speed, enabling effective design space exploration and early software development. Results demonstrate significant speedup over traditional simulation methods. Future work includes extending capabilities for comprehensive cloud data center simulations.

#system simulation of 1000-cores heterogeneous socs #system simulation of 1000-cores heterogeneous socs ppt #powerpoint #presentation
System Simulation Of 1000-cores Heterogeneous SoCs - slide 1
01 / 21System Simulation Of 1000-cores Heterogeneous SoCs
1 / 17

Télécharger la présentation

System Simulation Of 1000-cores Heterogeneous SoCs
Une image / un lien ci-dessous est fourni (tel quel) pour télécharger la présentation

Politique de téléchargement : le contenu du site vous est fourni TEL QUEL pour votre information et votre usage personnel ; il ne peut être vendu, concédé sous licence ni partagé sur d’autres sites sans l’accord de son auteur.Le contenu vous est fourni TEL QUEL, pour votre information et votre usage personnel uniquement. Téléchargez la présentation en cliquant sur ce lien. Lors du téléchargement, si vous ne parvenez pas à télécharger une présentation, l’éditeur a peut-être supprimé le fichier de son serveur.Pendant le téléchargement, si vous ne parvenez pas à obtenir une présentation, le fichier a peut-être été supprimé par l’éditeur.

F I N

Plus de contenu associé

Transcription de la présentation

  1. System Simulation Of 1000-cores Heterogeneous SoCs Shivani Raghav Embedded System Laboratory (ESL) EcolePolytechniqueFederale de Lausanne (EPFL)

  2. Price profile N Price profile 1 Load profile N Load profile 1 w $ $ w now now now now ESL Work on Energy-Aware Datacenter Design Datacenter infrastructure PMSM: Power/Therm. Manager IPS IPS IPS communic. Internet IPS network IPS Grid Load profile 1, 2 and 3 New server cooling tech. IPS System Simulationfor many-core SIMinG-1k

  3. Emerging Data-Intensive Workloads Financial Simulations Medical Imaging Cloud Servers Monte Carlo Simulations Molecular Dynamics Gene Sequencing Online Gaming Services

  4. Demand for Hardware Acceleration Hybrid Cores AMD Fusion (on-chip) GPU Clusters (off –chip Accelerators) Tile based Manycores Intel SCC, Tile 64 (Integrated)

  5. Urgent Need for Simulation of Heterogeneous SoCs Thermal & Power Evaluations Design Space Exploration Simulation Benchmarking Profiling Debugging Early Software Development

  6. How to Design a Fast and Scalable Many-Core Simulator? Parallel Target Parallel Simulator Parallel Host

  7. Simulating Parallel Target on Parallel Host WWT II Graphite Cotson, OVPSim Flexus RAMP Opportunity Large Parallel Systems FPGA GPGPU is an Old Technology…

  8. Target Architecture Switch Memory Caches Core Data-Parallel Coprocessors Simple In-order Cores 1000s of cores in a tile network Fine grain parallelism

  9. Solution – Accelerating Simulation using GPGPUs Target Architecture Host Platform A Perfect Match

  10. Outline • Problem Overview Simulation of Heterogeneous SoCs • Solution SIMinG-1k: A GPU accelerated simulator • Evaluation • Summary

  11. Overall Simulation Framework Data Parallel Code Sequential Code Application General Purpose CPU Target Architecture Many-Core Accelerator SIMinG-1k Simulator Host Platform

  12. SIMinG-1k - Features • Instruction Accurate • Inexpensive and EasilyAvailable • FastDevelopment Cycle • Equation Performance Model • Portability (Target Independent) • Interpretation basedcore-simulation

  13. Challenges of using GPU as a host SIMT(Single inst multiple threads) Divergent Code isa problem Synchronizationoutside thread block Slow CPU-GPU communication Global Memory is slow and limited

  14. Outline • Problem Overview Simulation of Heterogeneous SoCs • Solution SIMinG-1k (GPU accelerated simulator) • Evaluation • Summary

  15. Results – Architecture 1 Data Scratchpad ARM ISA Inst Scratchpad Single tileof target Accelerator MIPS - Number of simulated instruction in host wall clock time

  16. Speed Up – Architecture 1 Speedup compared to simulation on OVPSim (thousands of ARM cores)

  17. Results – Architecture 2 Switch Single tile of Data-parallel Accelerator (cores, caches, on-chip interconnect) Memory Caches Core

  18. Speed Up – Architecture 2 Speedup compared to serial simulation on QEMU

  19. Outline • Problem Overview Simulation of Heterogeneous SoCs • Solution SIMinG-1k (GPU accelerated simulator) • Evaluation • Summary

  20. Conclusion Future Work • Extend the simulator for thermal and power evaluations • Complete simulation of Cloud Data Centers • Challenge Fast and parallel simulator for heterogeneous SoCs • Solution Parallelize 1000 core simulation using GPUs • Design Full System Simulation using QEMU and SIMinG-1k • Results High Scalability and speedup upto 4096 cores

  21. Thanks! Questions?