why can't Multicore-TSNE speed up my experiment with mnist

[yuxiaokang-source]

my test code of Multicore-TSNE is below

%%time
import numpy as np
from MulticoreTSNE import MulticoreTSNE as TSNE
from matplotlib import pyplot as plt
if __name__ == "__main__":
    data=np.load("/DATA1/zhangjingxiao/yxk/dataset/mnist/mnist.npz")
    for item in data.files:
        print(item)# find keys，the you can get value
        print(data[item].shape)
        print("=================")
    ## follow this

    X=data["x_train"].reshape(60000,-1)
    y=data["y_train"]
    print(X.shape)

    embeddings=TSNE(n_jobs=8).fit_transform(X)
    vis_x=embeddings[:,0]
    vis_y=embeddings[:,1]
    plt.scatter(vis_x,vis_y,c=y)
    plt.show()

my result is

my test code of TSNE in sklearn is

%%time
import numpy as np
from sklearn.manifold import TSNE 
#from MulticoreTSNE import MulticoreTSNE as TSNE
from matplotlib import pyplot as plt

data=np.load("/DATA1/zhangjingxiao/yxk/dataset/mnist/mnist.npz")
for item in data.files:
    print(item)# find keys，the you can get value
    print(data[item].shape)
    print("=================")
## follow this

X=data["x_train"].reshape(60000,-1)
y=data["y_train"]
print(X.shape)

tsne = TSNE(n_components=2, init='pca', random_state=0)
embeddings= tsne.fit_transform(X)
vis_x=embeddings[:,0]
vis_y=embeddings[:,1]
plt.scatter(vis_x,vis_y,c=y)
plt.show()

my result is below

It seems that mutlticore-tsne didnt speed up my experiment? Could you give me some advice about it ? Thank you