Meena Arunachalam#
Meena Arunachalam is a Fellow and Director at AMD, where she leads a team working on AI workload performance for AMD Instinct™ GPUs. Her focus includes optimizing end-to-end performance for data center inference and training, spanning MLPerf benchmarks and open-source GenAI models. She has authored over 20 technical papers and has contributed to strategies that improve the efficiency of AI systems. Meena also shares her perspectives on AI performance and optimization at industry conferences through invited talks and panels.
Posts by Meena Arunachalam
Reproducing AMD MLPerf Inference v6.1 Submission Results
In this blog, we share the technical details of how we accomplish the results in our MLPerf Inference v6.1 submission.
Technical Dive into AMD MLPerf Inference v6.1 Submission
Learn about the ROCm optimizations powering dlrm-v3, llama2-70b, and gpt-oss-120b performance.
Technical Dive into AMD's MLPerf Training v6.0 Submission
In this blog, we share the technical details of how we accomplish the results in our MLPerf Training v6.0 submission.
Reproducing AMD MLPerf Training v6.0 Submission Result
Learn how to reproduce AMD's MLPerf Training v6.0 submission result.
AMD Instinct™ GPUs MLPerf Inference v6.0 Submission
In this blog, we share the technical details of how we accomplish the results in our MLPerf Inference v6.0 submission.
Reproducing the AMD MLPerf Inference v6.0 Submission Result
Provide instructions to potential customers and partners to verify our MLPerf Inference v6.0 submission result.
Reproducing AMD MLPerf Training v5.1 Submission Result
Learn how to reproduce AMD's MLPerf Training v5.1 submission result.
Technical Dive into AMD MLPerf Training v5.1 Submission
Learn about the technical details of how AMD achieved the results in the MLPerf Training v5.1 submission.
Technical Dive into AMD's MLPerf Inference v5.1 Submission
In this blog, we share the technical details of how we accomplish the results in our MLPerf Inference v5.1 submission.
Reproducing the AMD Instinct™ GPUs MLPerf Inference v5.1 Submission
In this blog, we will provide step by step instruction on how to reproduce AMD's MLPerf Inference v5.1 Submission
Slim Down Your Llama: Pruning & Fine-Tuning for Maximum Performance
This blog describes the technical details of how we prune and fine tune the Llama 3.1 405B model in our MLPerf Inference v5.1 submission.
AMD’s MLPerf Training Debut: Optimizing LLM Fine-Tuning with Instinct™ GPUs
Explore the techniques we used to improve the training performance on MI300X and MI325X in our MLPerf Training 5.0 submission.
Reproduce AMD's MLPerf Training v5.0 Submission Result with Instinct™ GPUs
Follow this step-by-step guide to reproduce AMDs MLPerf 5.0 Training Submission with Instinct GPUs using ROCm
High-Throughput BERT-L Pre-Training on AMD Instinct™ GPUs: A Practical Guide
Learn how to optimize BERT-L training with mixed precision and Flash Attention v2 on AMD Instinct GPUs — follow our tested MLPerf-compliant step-by-step guide.
Reproducing the AMD Instinct™ GPUs MLPerf Inference v5.0 Submission
A step-by-step guide to reproducing AMD’s MLPerf v5.0 results for Llama 2 70B & SDXL using ROCm on MI325X
AMD Instinct™ MI325X GPUs Produce Strong Performance in MLPerf Inference v5.0
We showcase MI325X GPU optimizations that power our MLPerf v5.0 results on Llama 2 70B, highlighting performance tuning, quantization, and vLLM advancements.
Benchmarking Machine Learning using ROCm and AMD GPUs: Reproducing Our MLPerf Inference Submission
Benchmarking Machine Learning using ROCm and AMD GPUs: Reproducing Our MLPerf Inference Submission