HammerSim is a gem5-based full-system framework for modeling RowHammer with probability-driven bitflip simulation, validated against real DDR4 DIMMs via JS divergence.
A deeper look into rowhammer’s sensitivities: Experimental analysis of real dram chips and implications on future attacks and defenses,
5 Pith papers cite this work. Polarity classification is still indexing.
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EnergyLens predicts multi-GPU LLM inference energy consumption with 9-13% MAPE and identifies configurations with up to 52x energy efficiency differences.
Dooly reduces LLM inference profiling GPU-hours by 56.4% across 12 models while keeping simulation MAPE under 5% for TTFT and 8% for TPOT by making profiling configuration-agnostic and redundancy-aware.
EnergAIzer predicts module-level GPU utilization from structured kernel patterns and feeds it into a power model to estimate dynamic power with 8% error on Ampere GPUs and 7% on H100 forecasts.
Wattlytics is a public web platform that integrates benchmark-driven GPU performance scaling, DVFS-aware power modeling, and TCO analysis to support informed HPC cluster design and procurement decisions.
citing papers explorer
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HammerSim: A System-Level Tool to Model RowHammer
HammerSim is a gem5-based full-system framework for modeling RowHammer with probability-driven bitflip simulation, validated against real DDR4 DIMMs via JS divergence.
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EnergyLens: Predictive Energy-Aware Exploration for Multi-GPU LLM Inference Optimization
EnergyLens predicts multi-GPU LLM inference energy consumption with 9-13% MAPE and identifies configurations with up to 52x energy efficiency differences.
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Dooly: Configuration-Agnostic, Redundancy-Aware Profiling for LLM Inference Simulation
Dooly reduces LLM inference profiling GPU-hours by 56.4% across 12 models while keeping simulation MAPE under 5% for TTFT and 8% for TPOT by making profiling configuration-agnostic and redundancy-aware.
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EnergAIzer: Fast and Accurate GPU Power Estimation Framework for AI Workloads
EnergAIzer predicts module-level GPU utilization from structured kernel patterns and feeds it into a power model to estimate dynamic power with 8% error on Ampere GPUs and 7% on H100 forecasts.
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Wattlytics: A Web Platform for Co-Optimizing Performance, Energy, and TCO in HPC Clusters
Wattlytics is a public web platform that integrates benchmark-driven GPU performance scaling, DVFS-aware power modeling, and TCO analysis to support informed HPC cluster design and procurement decisions.