from collections import deque
MOD = 998244353

class FFT:
    inv_ = [1]

    def __init__(self, MOD=998244353):
        FFT.MOD = MOD
        g = self.primitive_root_constexpr()
        ig = pow(g, FFT.MOD - 2, FFT.MOD)
        FFT.W = [pow(g, (FFT.MOD - 1) >> i, FFT.MOD) for i in range(30)]
        FFT.iW = [pow(ig, (FFT.MOD - 1) >> i, FFT.MOD) for i in range(30)]

    def primitive_root_constexpr(self):
        if FFT.MOD == 998244353:
            return 3
        elif FFT.MOD == 200003:
            return 2
        elif FFT.MOD == 167772161:
            return 3
        elif FFT.MOD == 469762049:
            return 3
        elif FFT.MOD == 754974721:
            return 11
        divs = [0] * 20
        divs[0] = 2
        cnt = 1
        x = (FFT.MOD - 1) // 2
        while x % 2 == 0:
            x //= 2
        i = 3
        while i * i <= x:
            if x % i == 0:
                divs[cnt] = i
                cnt += 1
                while x % i == 0:
                    x //= i
            i += 2
        if x > 1:
            divs[cnt] = x
            cnt += 1
        g = 2
        while 1:
            ok = True
            for i in range(cnt):
                if pow(g, (FFT.MOD - 1) // divs[i], FFT.MOD) == 1:
                    ok = False
                    break
            if ok:
                return g
            g += 1

    def fft(self, k, f):
        for l in range(k, 0, -1):
            d = 1 << l - 1
            U = [1]
            for i in range(d):
                U.append(U[-1] * FFT.W[l] % FFT.MOD)
            
            for i in range(1 << k - l):
                for j in range(d):
                    s = i * 2 * d + j
                    f[s], f[s + d] = (f[s] + f[s + d]) % FFT.MOD, U[j] * (f[s] - f[s + d]) % FFT.MOD

    def ifft(self, k, f):
        for l in range(1, k + 1):
            d = 1 << l - 1
            for i in range(1 << k - l):
                u = 1
                for j in range(i * 2 * d, (i * 2 + 1) * d):
                    f[j+d] *= u
                    f[j], f[j + d] = (f[j] + f[j + d]) % FFT.MOD, (f[j] - f[j + d]) % FFT.MOD
                    u = u * FFT.iW[l] % FFT.MOD

    def convolve(self, A, B):
        n0 = len(A) + len(B) - 1
        k = (n0).bit_length()
        n = 1 << k
        A += [0] * (n - len(A))
        B += [0] * (n - len(B))
        self.fft(k, A)
        self.fft(k, B)
        A = [a * b % FFT.MOD for a, b in zip(A, B)]
        self.ifft(k, A)
        inv = pow(n, FFT.MOD - 2, FFT.MOD)
        A = [a * inv % FFT.MOD for a in A]
        del A[n0:]
        return A

# [x ^ n] P(x) / Q(x)
def BostanMori(P, Q, n):
    fft = FFT()
    while n:
        R = [(x * (-1) ** (i % 2)) % MOD for i, x in enumerate(Q)]
        Q = fft.convolve(Q, R[:])[::2]
        P = fft.convolve(P, R[:])[n % 2::2]
        n >>= 1
    return P[0] * pow(Q[0], MOD - 2, MOD) % MOD

n, m = map(int, input().split())
if m == 1:
    print(0)
    exit()
queue = deque()
fft = FFT()
for i in range(2, m + 1):
    q = [1] * (i + 1)
    q[i] = -1
    p = [1] * i
    p[0] = 0
    queue.append((p, q))

while len(queue) >= 2:
    p1, q1 = queue.popleft()
    p2, q2 = queue.popleft()
    l1 = len(q1)
    l2 = len(q2)
    nq = fft.convolve(q1[:], q2[:])
    np1 = fft.convolve(p1, q2)
    np2 = fft.convolve(p2, q1)
    assert len(np1) == len(np2)
    np = [(p1 + p2) % MOD for p1, p2 in zip(np1, np2)]
    queue.append((np, nq))

P, Q = queue.popleft()
Q_P = Q[:] + [0] * (len(P) - len(Q))
for i, p in enumerate(P):
    Q_P[i] -= p
    Q_P[i] %= MOD
ans = BostanMori(Q, Q_P, n)
print(ans)

"""
(1 + x - x^2) / (1 - x^2)

(1 + x - x^2) / (2 + x - 2x^2)


(1 + x + x^2 - x^3) / (1 - x^3)

(1 + x + x^2 - x^3) / (2 + x + x^2 - 2x^2)

"""