Open In App

Differences between Single Datapath and Pipeline Datapath

Improve
Improve
Like Article
Like
Save
Share
Report

1. Single Cycle Datapaths : Single Datapaths is equivalent to the original single-cycle datapath The data memory has only one Address input. The actual memory operation can be determined from the MemRead and MemWrite control signals. There are separate memories for instructions and data There are 2 adders for PC-based computations and one ALU. The control signals are the same. 

2. Pipeline Datapaths : The goal of pipelining is to allow multiple instructions to be executed at the same time. We may need to perform several operations in a cycle. Increment the PC and add registers at the same time. Fetch one instruction while another one reads or writes data. Like the single-cycle datapath, a pipeline processor needs to duplicate hardware elements that are needed in the same clock cycle. 

Differences between Single Datapath and Pipeline Datapath :

S.No. Single Cycle Datapath Pipeline Datapath
1 Instructions are not subdivided Instructions are divided into one per stage
2 Clock cycles are long enough for the lowest instruction Clock cycles are short but long enough for the lowest instruction
3 There are only 1 instruction that can be executed at the same time. There are as many instructions as pipeline stages
4 There is 1 cycle per instruction, i, e., CPI = 1 There is a fixed number of clock cycles per instruction, one for each pipeline stage, i.e., CPI = k
5 Control unit generates signals for the entire instruction. Control unit generates signals for the entire instruction; these signals are propagated from one pipeline stage to another via the pipeline registers.
6 There is duplicate hardware, because we can use a functional unit for at most one subtask per instruction. There is duplicate hardware, so that there are no restrictions on which instructions can be in the pipeline simultaneously.
7 Extra registers are not required. Extra registers are required to provide the results of one pipeline stage to the next pipeline stage.
8 Performance is baseline. Performance is moderately faster to significantly faster than a single cycle.

Here’s an example code that demonstrates the differences between a single datapath and a pipeline datapath. We’ll focus on a simplified scenario where we perform arithmetic operations on data elements.

Let’s start by defining a single datapath implementation:

Python




# Single datapath implementation
def single_datapath(a, b, c):
    result = (a + b) * c
    return result


In the single datapath implementation, we perform two arithmetic operations: addition and multiplication. The operands ‘a‘ and ‘b‘ are added together, and the result is then multiplied by ‘c’.

Now, let’s define a pipeline datapath implementation:

Python




# Pipeline datapath implementation
def pipeline_datapath(a, b, c):
    # Stage 1: Addition
    stage1_result = a + b
 
    # Stage 2: Multiplication
    stage2_result = stage1_result * c
 
    return stage2_result


In the pipeline datapath implementation, we divide the computation into two stages. In the first stage, we perform the addition of ‘a’ and ‘b’ and store the intermediate result in ‘stage1_result’. In the second stage, we multiply ‘stage1_result’ by ‘c’ to obtain the final result, which is returned as ‘stage2_result’.

Now, let’s test both implementations with sample input values:

Python




# Test the implementations
a = 2
b = 3
c = 4
 
# Single datapath
single_result = single_datapath(a, b, c)
print("Single Datapath Result:", single_result)
 
# Pipeline datapath
pipeline_result = pipeline_datapath(a, b, c)
print("Pipeline Datapath Result:", pipeline_result)


In this code, we pass the values ‘a = 2′, ‘b = 3′, and ‘c = 4′ as input to both the single datapath and pipeline datapath implementations. We then print the results obtained from each implementation.

The output of the code will be as follows:

Single Datapath Result: 20
Pipeline Datapath Result: 20

Both the single datapath and pipeline datapath implementations yield the same result of ‘20′. However, the key difference lies in how the computations are divided and executed.

In the single datapath implementation, the addition and multiplication operations are performed sequentially, one after the other, in a single cycle. The entire computation is completed in a single step.

In the pipeline datapath implementation, the addition and multiplication operations are divided into separate stages. The addition is performed in the first stage, and the intermediate result is stored. In the second stage, the multiplication operation is performed using the intermediate result obtained from the previous stage. This allows for overlapping of the two operations and can potentially lead to improved performance in terms of throughput.

It’s important to note that this is a simplified example to illustrate the concept of single datapath and pipeline datapath. In real-world scenarios, datapaths can involve more complex operations and multiple stages, depending on the architecture and requirements of the system.



Last Updated : 21 Jul, 2023
Like Article
Save Article
Previous
Next
Share your thoughts in the comments
Similar Reads