MAHA: An Energy-Efficient Malleable Hardware Accelerator for Data-Intensive Applications

For data-intensive applications, energy expended in on-chip computation constitutes only a small fraction of the total energy consumption. The primary contribution comes from transporting data between off-chip memory and on-chip computing elements-a limitation referred to as the Von-Neumann bottleneck. In such a scenario, improving the compute energy through parallel processing or on-chip hardware...