Problem: You have a playlist consisting of n songs. The i-th song is characterized by two numbers t_i and b_i — its length and beauty respectively. The pleasure of listening to set of songs is equal to the total length of the songs in the set multiplied by the minimum beauty among them. For example, the pleasure of listening to a set of 3 songs having lengths [5, 7, 4] and beauty values [11, 14, 6] is equal to (5 + 7 + 4) ⋅ 6 = 96.

You need to choose at most k songs from your playlist, so the pleasure of listening to the set of these songs them is maximum possible.

Input

The first line contains two integers n and k (1 ≤ k ≤ n ≤ 3 ⋅ 10^5) – the number of songs in the playlist and the maximum number of songs you can choose, respectively.

Each of the next n lines contains two integers t_i and b_i (1 ≤ t_i, b_i ≤ 10^6) — the length and beauty of i-th song.

Output

Print one integer — the maximum pleasure you can get.

Examples

Input


4 3
4 7
15 1
3 6
6 8


Output


78


Input


5 3
12 31
112 4
100 100
13 55
55 50


Output


10000

Note

In the first test case we can choose songs {1, 3, 4}, so the total pleasure is (4 + 3 + 6) ⋅ 6 = 78.

In the second test case we can choose song 3. The total pleasure will be equal to 100 ⋅ 100 = 10000.

Solution (in PYTHON):

Solution:
"Template made by : https://codeforces.com/profile/c1729 , github repo : https://github.com/cheran-senthil/PyRival"
from __future__ import division, print_function
import bisect
import math
import itertools
import sys
from atexit import register



from heapq import heappush, heappop, heapify  
  
# heappop - pop and return the smallest element from heap 
# heappush - push the value item onto the heap, maintaining 
#             heap invarient 
# heapify - transform list into heap, in place, in linear time 
  
# A class for Min Heap 
class MinHeap: 
      
    # Constructor to initialize a heap 
    def __init__(self): 
        self.heap = []  
  
    def parent(self, i): 
        return (i-1)/2
      
    # Inserts a new key 'k' 
    def insertKey(self, k): 
        heappush(self.heap, k)            
  
    # Decrease value of key at index 'i' to new_val 
    # It is assumed that new_val is smaller than heap[i] 
    def decreaseKey(self, i, new_val): 
        self.heap[i]  = new_val  
        while(i != 0 and self.heap[self.parent(i)] > self.heap[i]): 
            # Swap heap[i] with heap[parent(i)] 
            self.heap[i] , self.heap[self.parent(i)] = ( 
            self.heap[self.parent(i)], self.heap[i]) 
              
    # Method to remove minium element from min heap 
    def extractMin(self): 
        return heappop(self.heap) 
  
    # This functon deletes key at index i. It first reduces 
    # value to minus infinite and then calls extractMin() 
    def deleteKey(self, i): 
        self.decreaseKey(i, float("-inf")) 
        self.extractMin() 
  
    # Get the minimum element from the heap 
    def getMin(self): 
        return self.heap[0] 

if sys.version_info[0] < 3:
    from io import BytesIO as stream
else:
    from io import StringIO as stream


if sys.version_info[0] < 3:
    class dict(dict):
        """dict() -> new empty dictionary"""
        def items(self):
            """D.items() -> a set-like object providing a view on D's items"""
            return dict.iteritems(self)

        def keys(self):
            """D.keys() -> a set-like object providing a view on D's keys"""
            return dict.iterkeys(self)

        def values(self):
            """D.values() -> an object providing a view on D's values"""
            return dict.itervalues(self)

    input = raw_input
    range = xrange

    filter = itertools.ifilter
    map = itertools.imap
    zip = itertools.izip

def reverse_insort(a, x, lo=0, hi=None):
    """Insert item x in list a, and keep it reverse-sorted assuming a
    is reverse-sorted.

    If x is already in a, insert it to the right of the rightmost x.

    Optional args lo (default 0) and hi (default len(a)) bound the
    slice of a to be searched.
    """
    if lo < 0:
        raise ValueError('lo must be non-negative')
    if hi is None:
        hi = len(a)
    while lo < hi:
        mid = (lo+hi)//2
        if x > a[mid]: hi = mid
        else: lo = mid+1
    a.insert(lo, x)
def sync_with_stdio(sync=True):
    """Set whether the standard Python streams are allowed to buffer their I/O.

    Args:
        sync (bool, optional): The new synchronization setting.

    """
    global input, flush

    if sync:
        flush = sys.stdout.flush
    else:
        sys.stdin = stream(sys.stdin.read())
        input = lambda: sys.stdin.readline().rstrip('\r\n')

        sys.stdout = stream()
        register(lambda: sys.__stdout__.write(sys.stdout.getvalue()))

def main():
    n,k=map(int,input().split())
    l1=[]
    for i in range(0,n):
        t,b=map(int,input().split())
        l1.append((b,t,i))
    l1.sort()
    l1=l1[::-1]
    sumt=[]
    heapObj = MinHeap()
    maxans=0
    for i in range(0,n):
        if i==0:
            heapObj.insertKey(l1[i][1])
            sumt.append(l1[i][1])
            maxans=sumt[i]*l1[i][0]
        else :
            if i<=k-1:
                sumt.append(sumt[i-1]+l1[i][1])
                maxans=max(maxans,l1[i][0]*sumt[i])
                heapObj.insertKey(l1[i][1])
            else :
                if l1[i][1]>heapObj.getMin():
                    sumt.append(sumt[i-1]-heapObj.getMin()+l1[i][1])
                    maxans=max(maxans,l1[i][0]*sumt[i])
                    heapObj.extractMin()
                    heapObj.insertKey(l1[i][1])
                else :
                    sumt.append(sumt[i-1])
    print(maxans)
        
    
if __name__ == '__main__':
    sync_with_stdio(False)
    main()