Andrew Wafaa
From Model to Metal: An Open Source Stack for Accelerating Intelligence
#1about 3 minutes
The challenge of a fragmented AI software stack
The proliferation of AI workloads across diverse hardware has created a fragmented ecosystem with vendor-specific libraries and duplicated optimization efforts.
#2about 3 minutes
Unifying AI development with the UXL Foundation
The UXL Foundation leverages Intel's oneAPI to create a unified, open-source library suite that ensures portability and performance across different hardware architectures.
#3about 3 minutes
Exploring core UXL components for compute and math
A breakdown of oneDNN for accelerating deep learning primitives and oneMKL for high-performance mathematical functions like BLAS and FFT.
#4about 2 minutes
Managing parallelism and data with UXL libraries
An overview of oneTBB for task scheduling, oneCCL for multi-node communication, and oneDAL for managing data analysis and machine learning pipelines.
#5about 2 minutes
Visualizing the end-to-end UXL software stack
The complete architecture shows how UXL libraries abstract hardware and accelerate operations for frameworks during training, inference, and serving.
#6about 3 minutes
The benefits of an open and unified AI stack
An open-source, unified stack increases developer productivity, fosters community innovation, and ensures software evolves in lockstep with new hardware releases.
#7about 1 minute
How to contribute to the UXL open source project
A call for developers to contribute kernels, join the UXL Foundation working groups, and share workloads to help grow the open ecosystem.
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