Lectures related to NIOS II - Avalon Bus

Explores cache memory design, hits, misses, and eviction policies in computer systems, emphasizing spatial and temporal locality.

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Memories: Evolution and Types

Explores the evolution and taxonomy of memories, focusing on SRAM and DRAM differences, memory layout, and functional taxonomy.

Direct-mapped and Annex Caches

Covers direct-mapped and annex caches in computer architecture, explaining cache structure, access patterns, hit rates, and latency calculations.

Parallel Port & Nios II Interrupts

Covers the design of a programmable parallel port interface for an Avalon bus and the architecture of the Nios II processor.

FPGA Programming with Speedgoat: Real-Time Signal Processing

Focuses on implementing a square function generator using Speedgoat FPGA technology and real-time signal processing techniques.

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Processor Architecture and System Design

Delves into RISC processor architecture, system design, microcontroller building blocks, and memory access.

Virtual Memory

Covers virtual memory, program relocation, memory protection, TLB, and memory hierarchy interactions.

Dynamic Binary Translation: Overcoming Binary Compatibility Challenges

Covers dynamic binary translation as a solution to binary compatibility issues in computer architectures.

Computer Architecture: Circuits and Processors

Introduces computer architecture, covering logic circuits, adders, processors, and performance optimization.

Introduction to Processors

Covers the fundamentals of processors, from digital logic to program execution, including components like ALU, register file, and control logic.

Automatic Synthesis of OS Code

Covers the automatic synthesis of OS code to ease the burden of developers in configuring translation hardware.

Computer Architecture: Electronic Memory (Transistor-based)

Explains electronic memory in computer architecture using transistor-based circuits for data storage and retrieval.

Instruction Set Extensions: High-Level Synthesis Techniques

Covers instruction set extensions and high-level synthesis techniques for optimizing embedded processors.

Deep Learning Building Blocks

Covers tensors, loss functions, autograd, and convolutional layers in deep learning.

General Introduction to Big Data

Covers data science tools, Hadoop, Spark, data lake ecosystems, CAP theorem, batch vs. stream processing, HDFS, Hive, Parquet, ORC, and MapReduce architecture.

Prediction and Speculation in Processor Design

Covers prediction and speculation techniques in processor design to enhance performance and reduce execution delays.

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