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Related lectures (30)

Explores the motivation and advantages of using GPUs for computation, focusing on their performance and programming through CUDA.

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Covers data-parallel operations in Scala programming, focusing on fold operations and aggregate operation.

Explores the evolution of transistors, power constraints, and the shift towards parallel computing in modern systems.

Covers matrix multiplication, properties, and the identity matrix in algebraic operations.

Covers the basics of Numpy, including importing the library, creating arrays, and performing linear algebra operations.

Explores polynomial operations, properties, and subspaces in vector spaces.

Explores futures as a structured approach to concurrency, simplifying parallel tasks and input-output operations.

Explores the group structure and isomorphism of elliptic curves, including inverses, associativity, and compactification to the torus.

Covers multiprocessor architecture, sustainable computing, AI model training impact, and parallel programming fundamentals.

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