Why Processors are Not Measured in MIPS

MIPS (Millions of Instructions Per Second) was once a popular measure of a processor's speed. However, in the modern world, this metric has become increasingly meaningless for several reasons. Let's explore why MIPS are no longer a reliable standard for evaluating processor performance.

MIPS vs. Modern Processor Capabilities

The primary issue with MIPS is the outdated perspective it provides. In the era when processors were measuring performance in MIPS, they were limited to a few million instructions per second. Today, processors can handle billions, if not trillions, of instructions per second.

Modern Floating Point Operations: Contemporary processors are designed to perform not just millions but billions or even trillions of floating point operations per second. Graphics processors (GPUs) are particularly potent, capable of executing trillions of operations in parallel. This stark contrast makes MIPS a poor metric for gauging current processor capabilities.

Caching and Performance Optimization

Another reason why MIPS has become meaningless is the use of multiple levels of cache in modern processors. These caches store frequently used data, reducing the number of times the CPU needs to access slower storage locations.

Caching Mechanism: When an operation is performed that goes through the CPU, the cache stores the result. The next time a similar operation is performed, the result is retrieved from the cache, bypassing the CPU entirely. This process, known as caching, significantly boosts performance and is a critical factor in modern computing. Therefore, measuring performance in terms of MIPS is misleading because it underestimates the true efficiency and speed of a processor.

Challenges in Defining an "Operation"

Another limitation of MIPS is the ambiguity associated with the term "operation." In computer science, an "operation" can encompass various tasks, each with varying complexities and execution times.

Variability in Task Complexity: Some operations take just a single clock cycle, while others can require multiple cycles or even entire computation sequences. This variability means that a raw MIPS count does not accurately reflect the overall performance of a processor.

Historical Context: MIPS was heavily referenced in discussions comparing Reduced Instruction Set Computing (RISC) and Complex Instruction Set Computing (CISC) processors. These comparisons, however, were more about marketing and theoretical benefits rather than practical implications.

Modern Performance Metrics

Given the limitations of MIPS, modern processor evaluation relies on a variety of metrics that better reflect real-world performance. Some of these metrics include:

Geometric Mean Scores: These scores provide a balanced view of performance across various workloads. Floating Point Operations per Second (FLOPS): Measures the number of floating point operations a processor can perform. Throughput and Latency: These measures assess how well a processor can handle a continuous stream of tasks (throughput) and the time it takes to complete a single task (latency). CPI (Cycles Per Instruction): This metric, although not as commonly used, provides insight into the efficiency of a processor's instruction set.

These metrics are crucial for evaluating the performance of today’s processors, as they offer a more accurate representation of real-world computational tasks.

Conclusion

While MIPS was once a useful metric for comparing processors, its inherent limitations make it an unreliable standard for modern computing. The combination of multiple levels of cache, variability in task execution time, and the high performance standards of contemporary processors means that more sophisticated metrics are now necessary to accurately assess and compare processor performance.