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World Congress 2024 • Aug 4, 2024 • Session details

WWC24 - Ankit Patel - Unlocking the Future Breakthrough Application Performance and Capabilities with NVIDIA

Ankit Patel

Ankit Patel reveals how NVIDIA GPUs slash deep learning costs by 98%. Master deploying composite AI architectures at scale without rewriting all your Python code.

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#1 about 3 min

Transitioning to accelerated computing for application developers

Moving beyond sequential CPU processing limits by adopting modular hardware structures for parallel execution.

#2 about 2 min

Demonstrating parallel processing capabilities and execution speeds

Comparing standard sequential execution limits against the rapid output capabilities of simultaneous GPU processing.

#3 about 2 min

Cost and power economics of hardware acceleration

Overcoming heavy infrastructure costs by calculating the return on investment when scaling accelerated deep learning workloads.

#4 about 3 min

Refactoring software applications with domain specific SDKs

Minimizing complex code refactoring by integrating specialized frameworks to accelerate mathematical equations and neural networks.

#5 about 3 min

Accelerating pandas dataframes using cudf module plugins

Upgrading performance bottlenecked Python scripts with module plugins capable of directing dataframe operators to GPUs.

#6 about 3 min

Evolving traditional coding logic into LLM prompting

Replacing rigid traditional programming functions with context-aware prompt instructions tailored for generative language models.

#7 about 4 min

Composing real time video flow applications utilizing multiple AI models

Connecting vision language algorithms with tool-capable instruction models to seamlessly compose multi-step AI video telemetry pipelines.

#8 about 3 min

Optimizing and deploying containerized AI inference workloads

Standardizing disparate cloud deployments through stable enterprise microservices configured for dynamic resource allocation and caching.

#9 about 2 min

Accessing API microservices and extensible developer training programs

Speeding up local iteration blocks by providing offline desktop access to foundational container environments and certification courses.

#10 about 3 min

Generating runtime optimizations across evolving physical hardware architectures

Sustaining high deployment throughput as underlying compute hardware shifts by automatically routing inference containers to optimally tuned runtimes.

Matching moments

2:33 min

Architecting CUDA and the AI software stack

Michael Kagan Michael Kagan +1 · World Congress 2026 Europe

2:08 min

History and scale of NVIDIA GPU computing

Paul Graham Paul Graham · LIVE

1:37 min

Accelerating compute with focused developer tools

Julia Koch Julia Koch +1 · World Congress 2026 Europe

3:42 min

Accelerating machine learning workloads using KleidiAI libraries

Andrew Wafaa Andrew Wafaa · World Congress 2024

3:17 min

Maximizing cloud native capabilities for scaling dynamic AI workloads

Jim Clark Jim Clark +3 · World Congress 2025

2:13 min

Amber's evolution as a pioneer in GPU acceleration

Thomas Schmidt Thomas Schmidt · World Congress 2024

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