test branch prediction

function t = testBranchPrediction()
    % data
    data = randi(256, [32768 1]);
    dataS = sort(data);

    % check results are equal
    v = {
        sum_conditional_if(data);
        sum_conditional_if(dataS);
        sum_conditional_continue(data);
        sum_conditional_continue(dataS)
    };
    assert(isequal(v{:}));

    % time
    t = zeros(4,2);
    feature accel on
    feature jit on
    t(1) = timeit(@() sum_conditional_if(data));
    t(2) = timeit(@() sum_conditional_if(dataS));
    t(3) = timeit(@() sum_conditional_continue(data));
    t(4) = timeit(@() sum_conditional_continue(dataS));
    feature accel off
    feature jit off
    t(5) = timeit(@() sum_conditional_if(data));
    t(6) = timeit(@() sum_conditional_if(dataS));
    t(7) = timeit(@() sum_conditional_continue(data));
    t(8) = timeit(@() sum_conditional_continue(dataS));
end

function s = sum_conditional_if(data)
    s = 0;
    for i=1:1e2
        for c=1:numel(data)
            if data(c) >= 128
                s = s + data(c);
            end
        end
    end
end

function s = sum_conditional_continue(data)
    s = 0;
    for i=1:1e2
        for c=1:numel(data)
            if data(c) < 128
                continue;
            end
            s = s + data(c);
        end
    end
end