Podcast Episode Details
Back to Podcast Episodes
Optimizing AI Inference on Non-GPU Architectures by Rajalakshmi Srinivasaraghavan
This story was originally published on HackerNoon at: https://hackernoon.com/optimizing-ai-inference-on-non-gpu-architectures-by-rajalakshmi-srinivasaraghavan.
Rajalakshmi Srinivasaraghavan drives AI innovation by optimizing inference on CPUs, making AI faster, scalable, and more accessible beyond GPUs.
Check more stories related to machine-learning at: https://hackernoon.com/c/machine-learning.
You can also check exclusive content about #ai-inference-optimization, #cpu-ai-performance, #non-gpu-ai, #scalable-ai-systems, #rajalakshmi-srinivasaraghavan, #high-performance-computing, #sustainable-ai-infrastructure, #good-company, and more.
This story was written by: @kashvipandey. Learn more about this writer by checking @kashvipandey's about page,
and for more stories, please visit hackernoon.com.
While GPUs dominate AI, Rajalakshmi Srinivasaraghavan proves CPUs can deliver powerful, scalable AI inference. Her work in CPU optimizations boosted performance by up to 50%, automated CI pipelines, and enabled day-one readiness on new hardware. With a focus on mentorship and forward-looking design, she is shaping AI infrastructure that’s affordable, efficient, and accessible.
Published on 1 month, 3 weeks ago