Memory Architecture Exploration For Programmable Embedded Systems

Memory architecture plays a crucial role in the performance and efficiency of programmable embedded systems. System designers must carefully analyze and explore different memory architectures to ensure optimal utilization of resources while meeting system design goals.

Understanding Memory Architecture

In simple terms, memory architecture refers to how the memory system is organized and designed in a programmable embedded system. It encompasses various aspects such as the types of memories used, their organization, access patterns, data transfer rates, and their interaction with the processor.

The memory architecture directly impacts the overall system performance, power consumption, and cost. Hence, it is essential to explore and determine the most suitable memory architecture for a specific application.

Memory Architecture Exploration for Programmable Embedded Systems

by Peter Grun (2002nd Edition, Kindle Edition)

4 out of 5

Language	:	English
Text-to-Speech	:	Enabled
File size	:	2221 KB
Screen Reader	:	Supported
Print length	:	145 pages

FREE

Factors Affecting Memory Architecture

Several factors influence the choice and exploration of memory architecture:

• Memory Requirements: The type and size of memory required for the application significantly impact the overall design. Different applications may have varying demands for read/write speeds, storage capacity, and data retention.
• Performance: The desired performance level, including latency and bandwidth requirements, influences the design of the memory architecture.
• Power Consumption: Embedded systems often operate on limited power sources and need to optimize energy usage. The memory architecture choice affects power consumption, so it should be carefully considered.
• Cost: The memory architecture directly affects the cost of the overall system. Designers need to strike a balance between performance and cost.
• Scalability: Future scalability and upgradability of the system should be taken into account while exploring memory architectures.

Exploration Techniques

Memory architecture exploration involves evaluating various design options and analyzing their implications. Here are some commonly used techniques:

1. Simulation: Simulation tools are used to model and simulate different memory architectures. Designers can assess their impact on system performance, power consumption, and cost. Simulations help in identifying bottlenecks and trade-offs.
2. Profiling: Profiling the application provides insights into memory usage patterns, including data access frequencies, memory contention, and hotspots. This information aids in making informed decisions about memory architecture.
3. Benchmarking: Running benchmark applications on different memory architectures allows for a comparative analysis. Performance metrics, such as execution time and energy consumption, are measured to evaluate the suitability of each design.
4. Experimentation: Building prototypes with different memory architectures helps validate assumptions and verify the expected benefits. It provides real-world data to support the exploration process.

Types of Memory Architectures

There are various types of memory architectures commonly used in programmable embedded systems:

1. Von Neumann Architecture: In this classical architecture, program instructions and data share the same memory space. This architecture simplifies system design but can lead to memory bottlenecks.
2. Harvard Architecture: In Harvard architecture, program instructions and data are stored separately, providing dedicated memory spaces. This architecture allows simultaneous instruction fetch and data access, improving overall system performance.
3. Modified Harvard Architecture: This architecture is a hybrid of Von Neumann and Harvard architectures. It combines the benefits of both, with separate instruction and data memories but allowing limited interactions.
4. Cach Read Architecture: This memory architecture includes multiple cache levels placed between the processor and main memory. Caches improve system performance by storing frequently accessed data closer to the processor.
5. Shared Memory Architecture: Multiple processing elements or cores share a unified memory space in this architecture. It enables efficient communication between the cores but can lead to memory contention. Techniques such as memory partitioning or arbitration are employed to mitigate contention issues.

Memory architecture exploration is a critical step in designing efficient programmable embedded systems. By carefully analyzing memory requirements, performance goals, power consumption constraints, cost factors, and scalability needs, system designers can select the most appropriate architecture. Utilizing simulation, profiling, benchmarking, and experimentation techniques empowers designers to make informed decisions. The choice of memory architecture significantly impacts the system's overall performance, power consumption, and cost, making it essential to explore and optimize this aspect of system design.

Remember, selecting the right memory architecture can make all the difference in maximizing the efficiency and effectiveness of your programmable embedded system!

Memory Architecture Exploration for Programmable Embedded Systems

by Peter Grun (2002nd Edition, Kindle Edition)

4 out of 5

Language	:	English
Text-to-Speech	:	Enabled
File size	:	2221 KB
Screen Reader	:	Supported
Print length	:	145 pages

FREE

Memory Architecture Exploration for Programmable Embedded Systems addresses efficient exploration of alternative memory architectures, assisted by a "compiler-in-the-loop" that allows effective matching of the target application to the processor-memory architecture. This new approach for memory architecture exploration replaces the traditional black-box view of the memory system and allows for aggressive co-optimization of the programmable processor together with a customized memory system.
The book concludes with a set of experiments demonstrating the utility of this exploration approach. The authors perform architecture and compiler exploration for a set of large, real-life benchmarks, uncovering promising memory configurations from different perspectives, such as cost, performance and power.