8 Differences Between SIMD Vs MIMD Architecture

What are the Main Differences Between SIMD vs MIMD Architecture? This post evaluates the advantages and disadvantages of Single Instruction, Multiple Data (SIMD) and Multiple Instruction, Multiple Data (MIMD) architectures, two classifications within Flynn’s taxonomy of parallel computer architecture. The goal is to determine which architecture is superior based on a set of criteria: features, architecture design, and parallel computing efficacy.

Introduction

A Guide to Understanding SIMD vs MIMD Architecture; Michael J. Flynn developed an early classification system, Flynn’s taxonomy, to categorize parallel computers based on the number of concurrent instruction and data streams. The four classifications are SISD, SIMD, MISD, and MIMD. This evaluation will focus on SIMD vs MIMD Architecture.

SIMD (Single Instruction, Multiple Data): This architecture allows the same operation (instruction) to be performed repeatedly on multiple pieces of data simultaneously. Common applications include signal processing, and an example is retrieving multiple files at once.
MIMD (Multiple Instruction, Multiple Data): This architecture allows for multiple different actions (instructions) to be performed simultaneously on numerous data pieces. It is the most common type of parallel program, exemplified by various simultaneous mathematical calculations (like addition and multiplication).

To evaluate the two SIMD vs MIMD Architecture, the following areas will be assessed:

Architecture and Features: Comparing the structural and functional aspects of each design.
Risk Assessment: Evaluating security and performance risks; the architecture with fewer risks is considered superior.
Performance Metrics:
- Latency: The execution time for program execution; faster and more accurate instructions indicate better latency.
- Throughput: The number of tasks completed per unit time.
Key Architectural Evaluations:
- Usability: The elegance and clarity of interaction with the program.
- Reliability: The assurance of consistent performance according to specifications.
- Modifiability: The ability to change the design and still implement it effectively.
- Cost-Efficiency: A more affordable and efficient architecture is preferable.

Features Comparison

SIMD vs MIMD Architecture have distinct features:

Feature	SIMD (Single Instruction, Multiple Data)	MIMD (Multiple Instruction, Multiple Data)
Program/Processing Elements	Single program; processing elements operate simultaneously.	Multiple communication programs; processing elements operate asynchronously.
Program Storage	Only one copy of the program is stored.	Each processing element stores its own program.
Instruction Cost/Decoder	Lower instruction cost; only one decoder in the control unit.	One decoder assigned in each processing element.
Complexity & Cost	Simple architecture; low cost.	More complex architecture; higher cost than SIMD.
Size & Performance	Smaller size; scalable in size and performance.	Larger size; much better performance.
Conditional Statements	Dependent on local data; all instructions of ‘then’ block must broadcast, followed by ‘else’ block.	More efficient execution; each processor can independently follow decision paths.
Synchronization	Implicit in the program; automatic synchronization of “send” and “receive” operations.	Explicit data structures, synchronization, operations, and identification protocols are needed.
Total Execution Time	Sum of maximal execution times through all processors.	Maximum execution time on a given processor.

Architecture Comparison

SIMD Architecture

SIMD architecture, though simpler in cost, is structurally complex:

Loop Controller: Generates control signals for long vector operations.
Functional Unit: Performs vector operations, communicating with the CPU.
Processors: Utilizes Array Processors (operating on multiple data elements at once) and Vector Processors (operating on multiple data elements in consecutive time steps).
- Vector Processor Advantages: Can have a deep pipeline, reduces instruction fetch bandwidth (as one instruction generates much work), and has a regular memory access pattern for high memory bandwidth.
- Vector Processor Disadvantage: Parallelism is only efficient with regular vector operations.
Compiler: A smart compiler is used for vectorizing instructions to turn them into machine language.
Efficiency & Issues: Efficient for arithmetic-intensive programs but suffers from data alignment problems, leading to extra time overhead that hinders automatic vectorization.
Memory Systems Supported: Supports single bank (only aligned accesses), multi-bank (enables unaligned and stride accesses with conflict limitation), and multi-port (capable of unaligned and stride accesses without limitations).

MIMD Architecture

MIMD architecture centers on grouped memory and processors:

Core Structure: Consists of a group of memory modules and processors.
Interconnection Network: Memory modules are accessed via a high-speed network connecting processing elements (processors) and memory elements via a switching element.
Address Space: The memory modules define a universal address space shared among processors.
Communication: Processing elements communicate by sending messages. Instructions can use any accessible data rather than being limited to a single, shared data stream.

Parallel Computing Implementation

MIMD Architecture in Parallel Computing

MIMD primarily uses thread and process-level architecture, allowing multiple threads to be executed in parallel.

Process Allocation: Each processor allocates an address space and loads the program’s process into it.
Transputer Breakthrough: An early parallel microprocessor with a built-in operating system, designed to be a low-cost, low-power complete processor.
Structure: The MIMD design is based on the von Neumann machine (single processor connected to a single memory module). To achieve parallelism, there are two primary options:
1. Distributed Memory (Option 1): Replace the processor/memory pairs (processing elements) and connect them via a network. No processing element can directly access the memory module of another; they communicate via message passing and are independent.
2. Shared Memory (Option 2): Create a set of processors and memory modules where each processor can access any memory module via a network. This defines a global address space that is shared (known as a dance-hall system). Processors and memory modules can communicate and share memory space. Shared memory MIMD utilizes multiprocessors, but accessing remote data takes more time due to distance.

Types of MIMD Parallel Computing

Type	Distributed Memory MIMD	Shared Memory MIMD
Description	Each processor has its own private memory. Computation must occur in local memory. Highly scalable.	All processors share a single memory system.
Memory	Local memory module. Highly scalable, building massive parallel computers.	Shared memory system. Lack of scalability.
Message Passing	Solves communication and synchronization well. No need for monitors.	Much easier to understand, as all information is in one location. Data can be accessed where it was composed.
User Responsibility	High responsibility: Must pay special attention to load balancing, avoid deadlock (where processes wait for each other), and partition code and data among processors. Requires a physical copy of data structures.	Low responsibility: No need to partition code or data; the system handles splitting large programs. No need to physically move data for communication.
Disadvantages	User responsible for load balancing and avoiding deadlock. Partitioning a large code base can be complex and error-prone.	Lack of scalability. Processors must wait for access rights to memory.

SIMD Architecture in Parallel Computing

SIMD parallel computing uses vector processing as its main memory system.

Vector Processor: A CPU that executes instructions operating on 1-D arrays (vectors).
CPU Components: Contains a control unit (directs processor operation), arithmetic logic unit (performs calculations), and registers (holds data/instructions).
Vector Length: The number of data elements per vector.
Pipelining: Both instructions and data are pipelined to reduce decoding time.
Memory Architecture: Utilizes Memory to Memory architecture. Operands are fetched directly from main memory, routed to the functional unit, and results are written back to main memory.
Advantages:
- Achieves a high clock rate (independent of previous results).
- Fewer fetches and branches (one vector instruction performs much work), resulting in fewer mispredictions.
- Very low memory latency (accesses memory a block at a time).
- Lower cost compared to scalar counterparts.
Disadvantages:
- Works well only with highly or completely parallel data.
- Requires large blocks of data to be efficient.
- Poor performance on scalar data.
- High price for individual chips due to limited on-chip memory.
- Vectorizing data increases code complexity.
- High cost of design and low returns compared to superscalar microprocessors.

Evaluation and Conclusion

How to Choose Between SIMD vs MIMD Architecture; The evaluation criteria include risks, latency/throughput, cost/benefits, usability, reliability, and modifiability.

General Comparison:

SIMD: Generally faster, cheaper, smaller, and simpler. Cost is reduced by needing only one instruction decoder. Used for problems performing the same operation in parallel. Easier programming due to simple architecture and implicit synchronization.
MIMD: Generally slower, more expensive, larger, and more complex. Can compute multiple instructions and run multiple programs simultaneously, enabling multitasking and far more complex operations. Used for problems that break algorithms into separate, independent parts assigned to different processors. More flexible, effective for a wider range of algorithms.

Key Evaluation Points:

Aspect	SIMD (Advantage)	MIMD (Advantage)
Cost	Cheaper (single instruction decoder).	No added cost of a control unit (though individual processors are costly).
Control Flow/Scalar Ops	Control flow and many scalar operations can be overlapped on the control unit, giving a performance advantage.	Asynchronous nature results in a higher effective execution rate for variable-time instructions; a processor does not wait for all others to complete an instruction.
Programming	Easier to create, understand, and debug (single instruction stream, implicit synchronization). User is not concerned with relative timings.	Highly flexible; different operations can be performed on different processors (multiple threads of control). Explicit synchronization primitives (semaphores) provide better control.

Conclusion on Superior Architecture

SIMD vs MIMD Architecture; Which Architecture Fits Your Needs? MIMD is the better architecture compared to SIMD.

Overall: MIMD is more expensive but performs much more complex programs and allows multitasking and multiple processes simultaneously. The two most prominent types of parallel computing (shared and distributed memory) belong to MIMD. By providing every processor its own memory, MIMD bypasses the downsides of SIMD’s single-instruction dependence, allowing each processor to operate independently and asynchronously.
Features: MIMD is superior because it handles multiple communication processes and processing elements independently. While more expensive, its much better performance is crucial for long, complex programs. The use of multiple instruction streams allows for more efficient execution of conditional statements. SIMD processors are dependent and cannot handle multiple or complex instructions well.
Architecture: MIMD excels as it allows multiple threads to be executed in parallel, with each instruction loaded into a separate, allocated memory space. This design represents the most familiar type of parallel processor (the von Neumann machine structure). SIMD, in contrast, suffers from data alignment problems that increase time overhead.

8 Differences Between SIMD vs MIMD Architecture

Comparative Analysis of SIMD vs MIMD Architecture: Differences