Calculate Cache Hit Ratio, Miss Ratio, and Effective Access Time
Traffic Metrics
Performance Metrics (Optional for EAT)
Total Requests:0
Cache Hit Rate:0%
Cache Miss Rate:0%
Effective Access Time (EAT):0
System Efficiency Status:Calculating…
function calculateCacheMetrics() {
// 1. Get Elements
var hitsInput = document.getElementById('chrc_hits');
var missesInput = document.getElementById('chrc_misses');
var hitTimeInput = document.getElementById('chrc_hit_time');
var missPenaltyInput = document.getElementById('chrc_miss_penalty');
var resultDiv = document.getElementById('chrc_results');
var errorDiv = document.getElementById('chrc_error_msg');
var eatRow = document.getElementById('row_eat');
// 2. Parse Values
var hits = parseFloat(hitsInput.value);
var misses = parseFloat(missesInput.value);
var hitTime = parseFloat(hitTimeInput.value);
var missPenalty = parseFloat(missPenaltyInput.value);
// 3. Validation
errorDiv.style.display = 'none';
resultDiv.style.display = 'none';
if (isNaN(hits) || isNaN(misses)) {
errorDiv.innerText = "Please enter valid numbers for Hits and Misses.";
errorDiv.style.display = 'block';
return;
}
if (hits < 0 || misses = 99) {
status = "Excellent (Highly Optimized)";
statusColor = "#2ea44f";
} else if (hitRatePct >= 90) {
status = "Good (Standard Performance)";
statusColor = "#0366d6";
} else if (hitRatePct >= 80) {
status = "Fair (Optimization Recommended)";
statusColor = "#d29922";
} else {
status = "Poor (Bottleneck Risk)";
statusColor = "#cb2431";
}
var statusEl = document.getElementById('res_status');
statusEl.innerText = status;
statusEl.style.color = statusColor;
resultDiv.style.display = 'block';
}
Understanding Cache Hit Rate and Efficiency
In computer architecture and system design, the Cache Hit Rate is a critical metric that measures how effectively a cache system (like a CPU cache, a CDN, or a database cache like Redis) fulfills requests. A high hit rate means the system serves data quickly from the high-speed cache rather than fetching it from slower main memory or disk storage.
How to Calculate Cache Hit Ratio
The formula to calculate the Cache Hit Ratio is straightforward. It compares the number of times data was found in the cache (Hits) against the total number of memory access attempts.
Formulas:
Total Requests = Cache Hits + Cache Misses
Hit Rate % = (Cache Hits / Total Requests) × 100
Miss Rate % = (Cache Misses / Total Requests) × 100
What is Effective Access Time (EAT)?
While the hit rate tells you the percentage of success, the Effective Access Time (EAT) tells you the real-world performance impact in time units (nanoseconds or milliseconds). It calculates the weighted average time it takes to access memory.
The formula for EAT is:
EAT = Hit Time + (Miss Rate × Miss Penalty)
Hit Time: The time to access the cache (usually very fast).
Miss Penalty: The time required to fetch data from the slower layer (e.g., RAM or Disk) and load it into the cache.
Why is a High Hit Rate Important?
Even a small improvement in hit rate can drastically improve system performance due to the disparity in speed between cache and main memory. For example, if a cache access takes 10ns and a memory access takes 100ns:
At 80% Hit Rate, EAT is roughly 30ns.
At 99% Hit Rate, EAT drops to roughly 11ns.
This calculator helps engineers and system administrators visualize these trade-offs to tune eviction policies (like LRU or LFU) and cache sizes for optimal throughput.