Pipelining

Pipelining

A technique that breaks down tasks into sequential stages for parallel processing, increasing throughput.

Common stages in CPU pipelines include Fetch, Decode, Execute, Memory, and Write-back.

Performance Gains

Throughput, rather than individual instruction speed, is improved.

Total execution time depends on the number of pipeline stages and the efficiency of each stage.

Pipelining does not enhance single-task latency but improves overall processing rate.

Hazards in Pipelining

Data Hazards

Control Hazards

Structural Hazards

Data hazards

Occur when an instruction depends on data from a previous instruction

Control hazard

Stem from branch instructions that may disrupt the pipeline.

Structural Hazards

Occur when two instructions require the same hardware simultaneously.

Pipeline Stalls

Caused by hazards; they introduce idle cycles, reducing throughput.

Minimizing stalls is essential for pipeline efficiency.

Branch Prediction

Used to minimize control hazards by predicting the outcome of branch instructions.

Techniques include static and dynamic branch prediction, with dynamic prediction leveraging branch history.

Superscalar Execution

Superscalar processors handle multiple instructions per cycle.

Out-of-Order Execution

Out-of-order execution improves efficiency by allowing instructions to execute as resources become available, respecting program order for accurate exceptions.

Pipeline Design Challenges

Adding more stages increases complexity and the potential for stalls.

Balance between instruction throughput and practical execution time.

Performance Metrics

Instruction throughput (instructions per second) and execution time.

Increased pipeline stages theoretically improve throughput but have practical limits due to hardware constraints.

how does pipelining improve system throughput?

increases the overall system throughput by processing several instructions simultaneously rather than completing one task before starting another

What are the typical stages of a CPU pipeline, and what is the function of each stage?

Typical stages include:

• Fetch (IF): Retrieves the next instruction from memory.

• Decode (ID): Decodes the fetched instruction and retrieves necessary operands.

• Execute (EX): Performs the operation or computation specified by the instruction.

• Memory Access (MEM): Reads from or writes data to memory if required.

• Write-back (WB): Writes the result back to the register file.

How does pipelining affect single instruction latency versus total workload processing rate?

Pipelining does not reduce the latency of individual instructions; each instruction still takes the same time to complete through all stages. However, by processing multiple instructions in parallel, pipelining significantly increases the overall processing rate (throughput), allowing more instructions to be completed in a given time.

What is a data hazard, and how can it cause a pipeline stall?

A data hazard occurs when an instruction depends on the result of a previous instruction that hasn’t completed yet. This dependency can cause a pipeline stall, as the following instruction must wait until the required data is available.

What techniques are used to resolve data hazards in a pipelined processor?

Techniques include operand forwarding, which forwards the result of an operation directly to the next instruction without waiting for it to be written back to the register, and instruction reordering to delay or perform other operations until the data becomes available.

Explain control hazards and how they impact pipelined execution.

Control hazards arise from branch instructions where the decision to branch depends on the outcome of a previous instruction. If a branch decision isn’t resolved, subsequent instructions in the pipeline might need to be discarded or stalled, disrupting the pipeline flow.

What role does branch prediction play in pipelining, and what are the differences between static and dynamic branch prediction?

Branch prediction helps minimize the impact of control hazards by guessing the outcome of a branch before it’s fully evaluated. Static branch prediction uses fixed assumptions (e.g., always predict that the branch will not occur), while dynamic branch prediction adapts based on the history of past branches, making more accurate predictions.

How does operand forwarding work to reduce data hazards?

Operand forwarding sends data directly from the output of one stage (like the ALU) to an input of another stage in the pipeline, bypassing the need to write the result to the register file first. This allows dependent instructions to proceed without waiting.

What is the impact of structural hazards on pipeline performance?

Structural hazards occur when two instructions require the same hardware resource simultaneously, causing a conflict. This conflict can stall one of the instructions, delaying its execution and reducing overall pipeline efficiency.

Why does pipelining not result in faster execution of individual instructions?

Each instruction still has to pass through all the stages in the pipeline, taking a fixed amount of time. Pipelining improves the rate at which instructions are completed but doesn’t reduce the time it takes for any single instruction to finish.

How does increasing the number of pipeline stages theoretically affect instruction throughput?

Increasing the number of pipeline stages should increase throughput by allowing more instructions to be in progress simultaneously. However, this theoretical gain is limited by practical factors like hazards and stage balancing.

Describe superscalar processing and how it differs from standard pipelining

Superscalar processing involves multiple execution units, allowing multiple instructions to start in the same cycle. Unlike standard pipelining, which executes one instruction per cycle, superscalar processors can handle several instructions per cycle, boosting throughput.

What is out-of-order execution, and how does it contribute to pipelining efficiency?

Out-of-order execution allows instructions to execute as soon as resources are available, rather than in strict program order. This improves efficiency by preventing idle execution units, while ensuring results are written in the correct order for program consistency.

How does delayed branching work, and what is its purpose in pipelined processors?

Delayed branching involves placing instructions that execute regardless of the branch outcome in the pipeline's “delay slots.” This reduces pipeline stalls by filling slots that would otherwise be wasted when branch instructions are pending.

What challenges arise with adding more stages to a pipeline?

More stages increase complexity, requiring more inter-stage buffering and control. They also increase the chance of stalls from hazards, leading to diminishing returns in throughput.

Why are simpler addressing modes preferred for pipelined processors?

Simple addressing modes reduce the chance of stalls, require fewer resources to decode, and allow the compiler to optimize the instruction flow more easily, improving pipeline efficiency.

How do hazards and pipeline stalls affect the overall performance of a pipelined processor?

Hazards can cause stalls, temporarily halting instructions and reducing throughput. The more stalls that occur, the closer the processor’s performance gets to non-pipelined execution rates.

Explain the concept of precise and imprecise exceptions in pipelined processors.

Precise exceptions ensure that instructions complete in program order, allowing easy recovery from exceptions. Imprecise exceptions may leave instructions partially complete, complicating recovery.

What factors limit the theoretical throughput gains from increasing pipeline stages?

Practical limits include increased chances of stalls, complexity in handling hazards, the time needed to "fill" and "drain" the pipeline, and hardware constraints like power and area.

How do superscalar processors handle multiple instructions per cycle?

Superscalar processors use multiple execution units and wider paths to memory/cache, allowing several instructions to be fetched, decoded, and executed in parallel within each clock cycle.