freq = gemx.getFreq()
test.test_perf(timePointKernel, total_operations,
total_parallel_operations, freq, 0, 0, 0)
if np.max(m_size) > 4096 and np.max(k_size) > 4096 and np.max(
n_size) > 4096:
print("Skip golden comparision because large matrix size")
else:
test.multiply_and_cmp(mat_C[3], mat_A[3], mat_C[2], mat_bias[3],
m_size[3], n_size[3], post_scale)
if __name__ == '__main__':
np.random.seed(123) # for reproducibility
test = GemmTest()
parser = gemx.processCommandLine()
args = parser.parse_args()
gemx.createGEMMHandle(args.xclbin, args.gemxlib, args.device,
args.numKernel)
m_size = np.array([512, 512, 2048, 128])
k_size = np.array([384, 512, 512, 2048])
n_size = np.array([128, 128, 128, 128])
test_perf_multi_gemm(4, m_size, k_size, n_size, 32764, 32764,
[1, 0]) # run performance measurement
gemx.printStats()
# size = 256
# while size < 16384:
# test_perf(32764, 32764, 0, size, size, size, [1,0])
# size = size * 2
gemx.getMat(mat_C[0])
gemx.getMat(mat_C[1])
gemx.getMat(mat_C[2])
gemx.getMat(mat_C[3])
timePointKernel.append(time.time()) # copy from FPGA
freq = gemx.getFreq()
test.test_perf(timePointKernel, total_operations,
total_parallel_operations, freq, 0, 0, 0)
test.multiply_and_cmp(mat_C[3], mat_A[3], mat_C[2], mat_bias[3], m_size[3],
n_size[3], post_scale)
if __name__ == '__main__':
np.random.seed(123) # for reproducibility
test = GemmTest()
args, xclbin_opts = gemx.processCommandLine()
gemx.createGEMMHandle(args, xclbin_opts)
for PE in range(int(xclbin_opts["GEMX_numKernels"])):
for i in range(15):
for j in range(15):
test.test_basic_randint(PE, xclbin_opts, [i, j], 1024)
# test.test_rand_basic (32764, 0, 5, [1,0]) # larger matrix size will lead to hw timeout error in regression test
test_multiInstrv1(32764, 512, 512, 128, True)
size = 256
while size < 8192:
test_perf_gemm(size, size, size) # run performance measurement
size = size * 2