In this paper we present fine-grained multithreaded algorithms and implementations for the Fast Fourier Transform (FFT) problem. The FFT problem has been formulated using two distinct approaches based on the dataflow concepts. The first approach, referred to as the receiver-initiated algorithm, realizes the FFAT iterations as a parent-child relationship while fully exploiting the underlying parallelism. The second approach, referred to as the sender-initiated algorithm, follows a data-flow model based on the producer-consumer style of programming and can be adopted to different architectural parameters for achieving high performance. The implementations of the proposed algorithms have been carried out on the EARTH (Efficient Architecture for Running THreads) platform. For both the algorithms, we analyze the ratio of remote vs local threads and study its impact on the experimental results. Our implementation results show that for certain block sizes on fixed problem size and machine size, the receiver-initiated approach performs better than the sender-initiated approach. For large number of processors, both the algorithms perform well, yielding execution times of only 10 msec for an input of 16 K data points on a 64 processor machine, assuming each processor running at 140 MHz clock speed.