Presentation
A RRAM-based High Energy-efficient Accelerator Supporting Multimodal Tasks for Virtual Reality Wearable Devices
DescriptionVirtual reality (VR) wearable devices can achieve immersive entertainment by fusing multi-modal tasks from various senses. However, constrained by the short battery life and limited hardware resources of VR devices, it is difficult to run multiple tasks simultaneously with different modals. Based on the above issues, we propose an energy-efficient accelerator that supports Multi-modal Tasks for VR devices, namely MTVR. We present a multi-task computing solution based on the flexible multi-task computing core design and efficient computing unit allocation strategy, which simultaneously achieves efficient work of multi-modal tasks. We have designed an early exit detector to skip invalid calculations, which saves energy greatly. In addition, a fine-grained tiny value skip method at multiplier and adder levels is proposed to save energy
further. We provide a hybrid RRAM and SRAM memory access scheme, reducing the external memory access (EMA). Through experimental evaluation, the multi-task computing core achieves an average computational utilization of 95%. When the invalid input ratio is 90%, energy saving brought by the early exit detector can reach 88%. The tiny value skip method further achieved 13% energy saving. A hybrid memory access scheme obtains a 98.9% EMA reduction. We deployed the MTVR accelerator in FPGA and self-designed RRAM, achieving energy efficiency of 3.6 TOPS/W, higher than other single-task accelerators.
further. We provide a hybrid RRAM and SRAM memory access scheme, reducing the external memory access (EMA). Through experimental evaluation, the multi-task computing core achieves an average computational utilization of 95%. When the invalid input ratio is 90%, energy saving brought by the early exit detector can reach 88%. The tiny value skip method further achieved 13% energy saving. A hybrid memory access scheme obtains a 98.9% EMA reduction. We deployed the MTVR accelerator in FPGA and self-designed RRAM, achieving energy efficiency of 3.6 TOPS/W, higher than other single-task accelerators.
Event Type
Research Manuscript
TimeThursday, June 272:15pm - 2:30pm PDT
Location3008, 3rd Floor
Embedded Systems
Embedded Memory and Storage Systems