Pipelining in Multi-Core Architectures
Understanding Pipelining
Pipelining
Pipelining is a technique that allows multiple instructions to be processed simultaneously by dividing the execution process into distinct stages. While one instruction is being executed, the next can be decoded, and a third can be fetched, all simultaneously, but in different stages of the pipeline.
Each stage performs a specific task, such as fetching, decoding, executing, or writing back results.Analogy
Pipelining is like an assembly line in a factory, where each worker (stage) performs a specific task on a product (instruction) before passing it to the next worker.
The Stages of Pipelining
- Fetch: Retrieve the instruction from memory.
- Decode: Interpret the instruction to determine the required operation.
- Execute: Perform the operation using the ALU or other components.
- Write-Back: Store the result in a register or memory.
Write-back is essential, without it, instruction results aren’t stored before the next ones rely on them.
NoteEach stage operates independently, allowing multiple instructions to be in different stages of execution simultaneously.
Pipelining in Multi-Core Architectures
In multi-core architectures, each core can have its own pipeline, enabling parallel processing of instructions across multiple cores.
- Independent Operation: Each core fetches, decodes, executes, and writes back instructions independently.
- Shared Resources: Cores may share higher-level caches (e.g., L3 cache) and main memory, requiring coordination to maintain data consistency.
Consider a team of chefs (multiple cores) in a kitchen, each with their own workstation (their pipeline).
- They (multiple cores) can work independently at their own stations on different dishes or different parts of the same dish.
- An individual can chop ingredients, while other ingredients are cooking and resting or being washed (pipeline).
- But, all chefs share the fridge and pantry (cache and memory).
When designing algorithms for multi-core processors, consider how tasks can be divided into smaller, independent units that can be processed in parallel by different cores.
How Pipelining Improves Performance
- Increased Throughput: By overlapping instruction execution, pipelining increases the number of instructions processed per unit of time.
- Reduced Idle Time: Each stage of the pipeline is continuously active, minimizing downtime.
- Parallel Execution: In multi-core systems, pipelining allows each core to work on different instructions simultaneously, further enhancing performance.
- Think of pipelining like a relay race, where each runner (stage) passes the baton (instruction) to the next runner as soon as their part is complete.
- This overlap ensures that the race progresses continuously without waiting for one runner to finish entirely before the next starts.
Multi-Threading
Multi-Threading
A thread is a lightweight process, the smallest unit a CPU schedules.
Multi-threading allows a single core to handle multiple threads by rapidly switching between them, sharing execution resources.
- Increases CPU utilisation per core
- Useful for web servers, AI, simulations
- Not true parallelism (threads share core resources)
One chef cooking two dishes, switching between them efficiently.
- Multi-core = more cooks
- Multi-threading = one cook juggles multiple dishes
Challenges of Pipelining in Multi-Core Architectures
- Data Hazards: Occur when instructions depend on the results of previous instructions still in the pipeline.
- Control Hazards: Arise from branch instructions that alter the flow of execution, potentially invalidating prefetched instructions.
