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authornasr <nsrddyn@gmail.com>2025-11-20 21:43:16 +0100
committernasr <nsrddyn@gmail.com>2025-11-20 21:43:16 +0100
commit409b76a88e589cbd7a8dfd9d0aad8152bb00d0bb (patch)
tree6c6648a8bc025901e57de36174068ebd5e4a5523 /src/main/scala/com/nsrddyn/ALU/Prime.scala
parente077e179d43e04c7365acf8d1cc5bcb55998e6bd (diff)
feature: implemented some basic benchmarking logic & enum for pass and test
Diffstat (limited to 'src/main/scala/com/nsrddyn/ALU/Prime.scala')
-rw-r--r--src/main/scala/com/nsrddyn/ALU/Prime.scala41
1 files changed, 41 insertions, 0 deletions
diff --git a/src/main/scala/com/nsrddyn/ALU/Prime.scala b/src/main/scala/com/nsrddyn/ALU/Prime.scala
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+++ b/src/main/scala/com/nsrddyn/ALU/Prime.scala
@@ -0,0 +1,41 @@
+package com.nsrddyn.alu
+
+
+import com.nsrddyn.tools.Benchmark
+
+class Prime() extends Benchmark {
+
+ /*
+ * Calculate all primes up to limit
+ * This should stress the ALU in someway,
+ * doing this in a predictable manner,
+ * will hopefully keep the cpu pipeline busy
+ * and that way stress the branch predictor
+ *
+ * math.sqrt(n) => a prime number has 2 factors, one of the factors
+ * of the prime numbers has to be smaller then n
+ * after that we check if the number is whole number and thereby checking if its a prime
+ *
+ */
+
+
+ /*
+ * TODO: I did the countrary of what i wanted to accieve with the is prime function
+ * We want the function to be less optimized so that the CPU has more work == more stress
+ */
+
+
+ def isPrime(n: Int): Boolean = {
+ if n <= 1 then false
+ else !(2 to math.sqrt(n).toInt).exists(i => n % i == 0)
+ }
+
+ def run(n: Int, result: Boolean): Unit = {
+
+ for i <- 0 to n do if isPrime(i) == result then println("true") else println("false")
+
+ }
+
+
+}
+