Machine Learning Architectures : Hardware, Software and Data

When people learn about computers, they learn about the major elements: CPU, Memory, I/O and Storage. You write programs that run one the CPU and load data into main memory. This is now only one part of the story.

These days you need to be aware of multi-core systems, competing chip designs, cloud computing, edge computing and increasingly parallel and heterogeneous runtime environments. To be a good modern software developer, you need to know more about hardware.

We will cover:

  • The changing deployment architectures for software systems
  • Moore's Law: The Past
  • Moore's Law: The Future
  • Multi-core systems
  • Popular ISAs: x86, ARM, RISC-V
  • Modern Computer Architectures
  • Alternate devices such as: GPUs, FPGAs, ASICs, TPUs
  • Emerging calls for IT Sovereignty
  • Compiler-oriented strategies for managing these differences

Brian Sletten

About Brian Sletten

Brian Sletten is a liberal arts-educated software engineer with a focus on forward-leaning technologies. His experience has spanned many industries including retail, banking, online games, defense, finance, hospitality and health care. He has a B.S. in Computer Science from the College of William and Mary and lives in Auburn, CA. He focuses on web architecture, resource-oriented computing, social networking, the Semantic Web, AI/ML, data science, 3D graphics, visualization, scalable systems, security consulting and other technologies of the late 20th and early 21st Centuries. He is also a rabid reader, devoted foodie and has excellent taste in music. If pressed, he might tell you about his International Pop Recording career.

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