Java signal processing: FFTs with bytecodes

This paper investigates the possibility of using Java as a language for Digital Signal Processing. We compare the performance of the Fast Fourier Transform using Java interpreters, compilers, and native execution. To characterize the Java language as a platform for signal processing, we have implemented a traditional FFT algorithm in both C and Java and compared their relative performance. Additionally, we have developed a Tensor algebra FFT library in both Matlab and Java. Each of the Tensor libraries has been coded to exploit the characteristics of the source language. Our results indicate that the latest Sun Solaris 2.6 Java platform can provide performance within 20% to 60% of optmized C code on short FFT computations. On longer FFT computations, Java is about a factor of 2 to 3 times less e cient than optimized C code. We anticipate this gap to narrow with better compiler technology and direct execution on Java processors such as the Delft-Java multithreaded processor.