I am using DPC++ to accelerate knn algorithm on FPGA device. The following code is the code I wrote for the euclidean distance. The problem is that the fpga_emulation works very well with no problems while running it on fpga hardware (Intel Arria 10 OneAPI) gives -nan for all values in the resulting buffer, which means something got wrong in the parallel_for lioop. But I can't find anything wrong about it and the emulation worked.
I am using Intel Devcloud platform.
std::vector<double> distance_calculation_FPGA(queue& q, const std::vector<std::vector<double>>& dataset, const std::vector<double>& curr_test) {
std::cout<<"convert 2D to 1D"<<std::endl;
std::vector<double>linear_dataset;
for (int i = 0; i < dataset.size(); ++i) {
for (int j = 0; j < dataset[i].size(); ++j) {
linear_dataset.push_back(dataset[i][j]);
}
}
std::cout<<"buffering"<<std::endl;
range<1> num_items{dataset.size()};
std::vector<double>res;
//std::cout << "im in" << std::endl;
res.resize(dataset.size());
buffer dataset_buf(linear_dataset);
buffer curr_test_buf(curr_test);
buffer res_buf(res.data(), num_items);
std::cout<<"submit a job"<<std::endl;
auto start = std::chrono::high_resolution_clock::now();
{
q.submit([&](handler& h) {
accessor a(dataset_buf, h, read_only);
accessor b(curr_test_buf, h, read_only);
accessor dif(res_buf, h, write_only, no_init);
h.parallel_for(num_items, [=](auto i) {
for (int j = 0; j < 5; ++j) {
dif[i] += (b[j] - a[i * 5 + j]) * (b[j] - a[i * 5 + j]);
}
// out << "i : " << i << " i[0]: " << i[0] << " b: " << b[0] << cl::sycl::endl;
});
}).wait();
}
auto finish = std::chrono::high_resolution_clock::now();
std::chrono::duration<double> elapsed = finish - start;
std::cout << "Elapsed time: " << elapsed.count() << " s\n";
/* Iterative distance calculation
for (int i = 0; i < dataset.size(); ++i) {
double dis = 0;
for (int j = 0; j < dataset[i].size(); ++j) {
dis += (curr_test[j] - dataset[i][j]) * (curr_test[j] - dataset[i][j]);
}
res.push_back(dis);
}
*/
return res;
}
Question on your usage, usually with something like a NaN obviously we are looking at uninitialized memory (or divide by 0 which you don't have). Is it possible the ranges are some how off on the FGPA and/or the values aren't properly initialized for the array incidies?
Sorry I know that's pretty basic, but without your dataset I'm not 100% sure I can reproduce it.