  We present results from parallelizing the unpacking and clustering steps of
the raw data from the silicon strip modules for reconstruction of charged
particle tracks. Throughput is further improved by concurrently processing
multiple events using nested OpenMP parallelism on CPU or CUDA streams on GPU.
The new implementation along with earlier work in developing a parallelized and
vectorized implementation of the combinatoric Kalman filter algorithm has
enabled efficient global reconstruction of the entire event on modern computer
architectures. We demonstrate the performance of the new implementation on
Intel Xeon and NVIDIA GPU architectures.
