ndslice, using a slice in place of T[] in template parameters

[Jay Norwood via Digitalmars-d-learn]

I cut this median template from Jack Stouffer's article and was 
attempting to use it in  a parallel function.  As shown, it 
builds and execute correctly, but it failed to compile if I 
attempting to use
medians[i] = median(vec,slb[task]);

in place of the
medians[i] = median(vec,dbuf[j .. k]);
Is there a cast needed?

================
import std.array : array;
import std.algorithm;
import std.datetime;
import std.conv : to;
import std.stdio;
import std.experimental.ndslice;

shared double[] medians;
double[] data;
shared double[] dbuf;
int numTasks;
const int smalld = 1000;
const int bigd = 10_000;
const int fulld = bigd*smalld;

/**
Params:
r = input range
buf = buffer with length no less than the number of elements in 
`r`
Returns:
median value over the range `r`
*/
T median(Range, T)(Range r, T[] buf)
{
    import std.algorithm.sorting: sort;

    size_t n;

    foreach (e; r) {
        buf[n++] = e;
    }

    buf[0 .. n].sort();
    immutable m = n >> 1;
    return n & 1 ? buf[m] : cast(T)((buf[m - 1] + buf[m]) / 2);
}


void f3() {
    import std.parallelism;
    auto sl = data.sliced(smalld,bigd);
    auto slb = dbuf.sliced(numTasks,bigd);
    foreach(i,vec; parallel(sl)){
        int task = taskPool.workerIndex;
        int j = task*bigd;
        int k = j+bigd;
        medians[i] = median(vec,dbuf[j .. k]);
    }
}


void main() {
    import std.parallelism;
    numTasks = taskPool.size+1;
    data = new double[fulld];
    dbuf = new double[bigd*numTasks];
    medians = new double[smalld];

    for(int i=0;i<fulld;i++){ data[i] = i/(fulld*1.0);}
    StopWatch sw3;

    sw3.start();
    f3() ;
    auto r3 = sw3.peek().msecs;
    writeln("medians parallel:",medians);

    writeln("parallel time medians msec:",r3);
}