Package jline.api.cache

Class Cache_erec

java.lang.Object

jline.api.cache.Cache_erec

public final class Cache_erec
extends Object

Method Summary

Modifier and Type	Method	Description
static Matrix	cache_erec(Matrix gamma, Matrix m)	Computes the cache miss rate using an exact recursive method.
static Matrix	cache_erec(Matrix gamma, Matrix m, Matrix sigma, Matrix k)	Computes the normalizing constant under per-list storage cost caps, E(m,k) = E_i(m,k) + sum_j m_j gamma_ij E_i(m-1_j, k-sigma_i 1_j), with the extra boundary E(m,k)=0 whenever some residual cap is negative.
static Matrix	cache_erec_aux(Matrix gamma, Matrix m, int k)	Auxiliary method for computing the cache miss rate using an exact recursive method.

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Method Details

cache_erec

public static Matrix cache_erec(Matrix gamma,
 Matrix m)

Computes the cache miss rate using an exact recursive method.

Parameters:

gamma - Matrix representing the cache access factors.

m - Matrix representing the cache capacity vector.

Returns:

Matrix containing the computed cache miss rates.

cache_erec

public static Matrix cache_erec(Matrix gamma,
 Matrix m,
 Matrix sigma,
 Matrix k)

Computes the normalizing constant under per-list storage cost caps, E(m,k) = E_i(m,k) + sum_j m_j gamma_ij E_i(m-1_j, k-sigma_i 1_j), with the extra boundary E(m,k)=0 whenever some residual cap is negative. See Casale-Gast, IEEE/ACM Trans. Networking 29(2), 2021, Sec. IX.

Parameters:

gamma - Matrix representing the cache access factors.

m - Matrix representing the cache capacity vector.

sigma - Item storage costs (sizes), one per item; null or empty for none.

k - Per-list storage cost caps, one per list; null or empty for none.

Returns:

Matrix containing the computed normalizing constant.

cache_erec_aux

public static Matrix cache_erec_aux(Matrix gamma,
 Matrix m,
 int k)

Auxiliary method for computing the cache miss rate using an exact recursive method.

Parameters:

gamma - Matrix representing the cache access factors.

m - Matrix representing the cache capacity vector.

k - Integer representing the current number of rows in the recursive step.

Returns:

Matrix containing the computed cache miss rates.