Advanced CPU Designs: Crash Course Computer Science #9

New Section

In this section, Carrie Anne introduces the topic of computer processors and their evolution over time.

Evolution of Computer Processors

• Computer processors have evolved from mechanical devices capable of one calculation per second to modern CPUs running at gigahertz speeds.

• Initially, processor speed was improved by enhancing the switching time of transistors. However, this approach had limitations in boosting performance for more complex operations.

• Modern computer processors have developed various techniques to enhance performance and execute sophisticated instructions efficiently. This includes specialized circuits for graphics operations, video decoding, encryption, and more.

• Instruction sets in processors have grown larger over time to accommodate new functionalities while maintaining backward compatibility with older instructions. For example, the Intel 4004 had 46 instructions, whereas modern processors have thousands of different instructions.

New Section

This section explores the challenges related to data transfer between RAM and the CPU and how caches help overcome these challenges.

Data Transfer Challenges and Caches

• High clock speeds and complex instruction sets create a challenge in getting data quickly into and out of the CPU. The bottleneck often lies in accessing data from RAM due to delays in transmission along data buses.

• To address this issue, caches are used as a small piece of memory located on the CPU chip itself. Caches are much faster than RAM but have limited storage capacity compared to gigabytes of RAM.

• When the CPU requests data from RAM, instead of retrieving just one value, a whole block of data is transmitted from RAM to cache. This is beneficial because computer data is often processed sequentially or accessed repeatedly within a certain range.

• Caches significantly speed up data access by providing the requested data in a single clock cycle, eliminating the need to go back and forth between the CPU and RAM. This reduces idle waiting time for the processor.

New Section

This section explains cache hits and cache misses, as well as how caches can be used as scratch space during complex calculations.

Cache Hits, Cache Misses, and Scratch Space

• When data requested from RAM is already stored in the cache, it is called a cache hit. The cache can provide the data to the CPU quickly without accessing RAM again.

• If the requested data is not present in the cache, it is called a cache miss. In this case, the CPU needs to retrieve the data from RAM, which takes more time compared to a cache hit.

• Caches can also be used as scratch space during longer or more complicated calculations. Intermediate values can be stored in the cache temporarily for faster access and processing by the CPU.

New Section

This section discusses the problem of data mismatch between cache and RAM, the use of dirty bits in caching, and the concept of instruction pipelining.

Cache Data Mismatch and Dirty Bits

• The cache's copy of data can become different from the real version stored in RAM.

• This mismatch is recorded using a special flag called the dirty bit for each block of memory stored in the cache.

• Synchronization occurs when the cache is full and a new block of memory is requested by the processor.

• Before erasing an old block to free up space, the cache checks its dirty bit. If it's dirty, the old block is written back to RAM before loading in the new block.

Instruction Pipelining

• Instruction pipelining improves CPU performance by parallelizing operations.

• It allows multiple instructions to be executed simultaneously instead of sequentially.

• This concept is illustrated with an analogy of washing sheets: sequential vs parallelized approach.

• In a pipelined design, different stages of instruction execution (fetch-decode-execute) can overlap, increasing throughput.

• Pipelining requires careful handling of dependencies between instructions to avoid problems like data inconsistency.

New Section

This section continues discussing instruction pipelining and introduces out-of-order execution as a technique used in high-end processors.

Parallel Execution in Processor Design

• Processors can apply parallel execution similar to instruction pipelining.

• While one instruction is being executed, another instruction can be decoded or fetched from memory simultaneously.

• This overlapping process ensures that all parts of the CPU are active at any given time, increasing throughput.

Hazards and Solutions

• Dependencies between instructions pose hazards in pipelined processors.

• Data dependencies require looking ahead and potentially stalling pipelines to avoid problems.

• High-end processors can dynamically reorder instructions with dependencies to minimize stalls, known as out-of-order execution.

• The circuits involved in these processes are complex but highly effective.

New Section

This section discusses hazards related to conditional jump instructions and introduces branch prediction as a technique used to minimize delays.

Conditional Jump Instructions

• Conditional jump instructions can change the execution flow of a program based on a value.

• A simple pipelined processor experiences long stalls when encountering jump instructions, waiting for the value to be finalized.

• High-end processors employ tricks to deal with this problem and minimize delays.

Speculative Execution and Branch Prediction

• Advanced CPUs use speculative execution to guess the outcome of upcoming jump instructions.

• Based on this guess, the pipeline is filled with instructions, allowing uninterrupted execution if the guess is correct.

• If the guess is wrong, a pipeline flush occurs, discarding speculative results and restarting from the correct point.

• CPU manufacturers have developed sophisticated branch prediction techniques that often achieve over 90% accuracy.

New Section

This section highlights how superscalar processors can execute multiple instructions per clock cycle and discusses idle areas in pipelined designs.

Superscalar Processors

• Superscalar processors can execute more than one instruction per clock cycle, increasing performance further than pipelining alone.

• During the execute phase in a pipelined design, certain areas of the processor may remain idle while other parts are active.

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Multi-Core Processors

This section discusses the concept of multi-core processors and their role in increasing performance by running multiple streams of instructions simultaneously.

Introduction to Multi-Core Processors

• Multi-core processors have multiple independent processing units inside a single CPU chip.

• They are similar to having multiple separate CPUs but with tightly integrated cores that can share resources like cache.

• Dual core or quad core processors are common examples of multi-core processors.

Advantages of Multi-Core Processors

• Running several streams of instructions at once increases performance.

• Allows for parallel execution of mathematical instructions.

• High-end computers, such as servers, often use multi-core processors to handle simultaneous tasks efficiently.

Need for More Processing Power

• In some cases, even multiple cores may not be enough to meet the computational requirements.

• Supercomputers are built with a large number of processors to handle complex calculations and simulations.

• The Sunway TaihuLight supercomputer in China has 40,960 CPUs, each with 256 cores, totaling over ten million cores.

Processing Power of Supercomputers

• The Sunway TaihuLight supercomputer can process 93 quadrillion floating-point math operations per second (FLOPS).

• It demonstrates the significant increase in processing power compared to desktop computers over the years.

Conclusion

This section concludes the discussion on the advancements in computer processors and their increased speed and processing power over time.

Increasing Speed and Performance

• Computer processors have significantly improved in terms of speed and performance over the years.

• Multi-core processors allow for parallel execution and increased throughput.

• Supercomputers with a massive number of processors provide immense computational power for complex tasks.

The transcript is already in English.