Minimizing Data Movement and Parameter Count Across the Machine Learning Stack

Name: Minimizing Data Movement and Parameter Count Across the Machine Learning Stack
Price: 126.75 AUD
Availability: BackOrder

Everything is a Matrix

By: Andrew Sabot

Write A Review

Hardcover | 2 July 2026

At a Glance

Format
Hardcover

Dimensions(cm)
24.0 x 16.8

Hardcover

$126.75

or 4 interest-free payments of $31.69 with

Available for Backorder. We will order this from our supplier however there isn't a current ETA.

This book provides a focused, research-forward guide to making large AI models efficient in practice and also presents an array of novel techniques to reduce memory footprint, accelerate computation, and improve overall hardware utilization. The author demonstrates that substantial efficiency gains can be achieved by rethinking how data is computed, stored, and compressed, with a special focus on matrices, the core computational structure underpinning both scientific computing and neural networks. Modern AI models run on huge grids of numbers (matrices/tensors), and their speed and affordability depend on how those numbers are arranged and processed on real hardware (GPUs/TPUs/CPUs). This book explains practical methods to skip unnecessary work (structured sparsity), move data efficiently (gather/scatter), and shrink models without losing accuracy (block distillation) so that AI systems can use less memory, less time, and less energy without sacrificing quality. In addition, the book shows how to turn algorithmic ideas into hardware-aware speedups on GPUs/TPUs. Readers will learn when sparsity pays off, how to schedule irregular workloads, and how to recover accuracy in compressed models. Case studies illustrate end-to-end design choices, evaluation, and pitfalls. The result is a coherent perspective that bridges theory, compilers/run times, and real-world deployment.

Shipping

	Standard Shipping	Express Shipping
Metro postcodes:	$9.99	$14.95
Regional postcodes:	$9.99	$14.95
Rural postcodes:	$9.99	$14.95

Orders over $79.00 qualify for free shipping.

How to return your order

At Booktopia, we offer hassle-free returns in accordance with our returns policy. If you wish to return an item, please get in touch with Booktopia Customer Care.

Additional postage charges may be applicable.