DiAG: A Dataflow-Inspired Architecture for General-Purpose Processors

The end of Dennard scaling and decline of Moore's law has prompted the proliferation of hardware accelerators for a wide range of application domains. Yet, at the dawn of an era of specialized computing, left behind the trend is the general-purpose processor that is still most easily programmed and widely used but has seen incremental changes for decades. This work uses an accelerator-inspired approach to rethink CPU microarchitecture to improve its energy efficiency while retaining its generality. We propose DiAG, a dataflow-based general-purpose processor architecture that can minimize latency by exploiting instruction-level parallelism or maximize throughput by exploiting data-level parallelism. DiAG is designed to support any RISC-like instruction set without explicitly requiring specialized languages, libraries, or compilers. Central to this architecture is the abstraction of the register file as register 'lanes' that allow implicit construction of the program's dataflow graph in hardware. At the cost of increased area, DiAG offers three main benefits over conventional out-of-order microarchitectures: reduced frontend overhead, efficient instruction reuse, and thread-level pipelining. We implement a DiAG prototype that supports the RISC-V ISA in SystemVerilog and evaluate its performance, power consumption, and area with EDA tools. In the tested Rodinia and SPEC CPU2017 benchmarks, DiAG configured with 512 PEs achieves a 1.18x speedup and 1.63x improvement in energy efficiency against an aggressive out-of-order CPU baseline.