NA-ROB: An Improved RISC-V Superscalar Processor Based on Enhanced Reorder Buffer Design

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NA-ROB: An Improved RISC-V Superscalar Processor Based on Enhanced Reorder Buffer Design

Introduction

In the pursuit of high-performance computing, superscalar processors play a pivotal role by enabling instruction-level parallelism through out-of-order execution. A critical component in such processors is the reorder buffer (ROB), which ensures that instructions complete and commit in the correct program order despite being executed out of sequence. However, traditional ROB designs face significant challenges, including capacity limitations and blocking issues caused by long-latency instructions. These constraints hinder the processor’s ability to maximize parallelism and efficiency.

This article presents NA-ROB, an enhanced superscalar processor architecture based on RISC-V that addresses these limitations through two key innovations: a zero-register allocation strategy and a dynamically adjustable cache structure called AROB. The zero-register allocation strategy optimizes ROB utilization by avoiding unnecessary entries for instructions without destination registers. Meanwhile, AROB dynamically partitions long-latency and short-latency instructions, reducing blocking and improving throughput. Experimental results demonstrate that NA-ROB achieves a 66% improvement in average instructions per cycle (IPC) and a 48% reduction in ROB blocking probability compared to conventional designs.

Background and Motivation

Superscalar processors enhance performance by executing multiple instructions per clock cycle, leveraging instruction-level parallelism. However, maintaining correctness in out-of-order execution requires mechanisms like the ROB to ensure sequential commit. The ROB tracks instructions in program order, holding their results until they can be safely written back to architectural registers. While effective, traditional ROB implementations suffer from inefficiencies.

First, ROB capacity constraints limit the number of in-flight instructions, restricting parallelism. When the ROB fills, new instructions stall, degrading performance. Second, long-latency instructions, such as memory accesses or multi-cycle operations, can block the ROB’s head entry, preventing subsequent instructions from retiring even if they have completed execution. This blocking wastes resources and reduces throughput.

Prior research has explored solutions such as checkpoint-based recovery, speculative retirement, and dynamic ROB resizing. However, these approaches often introduce hardware complexity, increase latency, or fail to fully mitigate blocking. NA-ROB addresses these shortcomings with a novel combination of architectural optimizations that improve efficiency without excessive overhead.

Zero-Register Allocation Strategy

A significant inefficiency in conventional ROB designs is the allocation of entries for instructions that do not require register renaming, such as no-operation (NOP) instructions, branches, and jumps. These instructions consume ROB entries unnecessarily, reducing available space for instructions that genuinely need renaming.

The zero-register allocation strategy eliminates this waste by segregating instructions without destination registers into a dedicated zero-register region (ZRR). This separation ensures that only instructions requiring register renaming occupy ROB entries. The strategy operates in three stages:

  1. Instruction Dispatch: During decode, the processor checks whether an instruction has a destination register. If renaming is unnecessary, the instruction is routed to the ZRR instead of the ROB.
  2. Execution: Instructions in the ROB proceed normally, with results written back to their allocated entries. ZRR instructions bypass register file updates, saving writeback bandwidth.
  3. Commit: Completed ROB entries are retired in order, while ZRR instructions are discarded after execution.

This approach reduces contention for ROB entries, allowing more parallel instruction execution. Although additional logic is required to classify instructions during dispatch, the benefits in throughput and resource utilization outweigh the modest hardware cost.

AROB: Dynamic Cache for Instruction Partitioning

To address long-latency instruction blocking, NA-ROB introduces AROB, an auxiliary buffer that dynamically adjusts its capacity between 32 and 64 entries. AROB separates long-latency instructions (e.g., multiplies, divides, memory operations) from short-latency instructions (e.g., arithmetic-logic unit operations), storing them in the ROB and AROB, respectively. This partitioning prevents long-latency instructions from occupying the ROB’s head entry and stalling subsequent instructions.

Instruction Grouping Mechanism

AROB employs a grouping mechanism to manage instruction retirement. The first instruction in a sequence is assigned a group identifier. Subsequent short-latency instructions inherit the same group ID until another long-latency or zero-register instruction is encountered, at which point the group ID increments. For example:
• A multiply (MUL) starts group 1.

• Subsequent ADD and SUB instructions remain in group 1.

• A branch (BEQ) with no destination register increments the group ID to 2 and is stored in the ZRR.

• A store (STORE) increments the group ID to 3 and is placed in the ROB.

This grouping ensures that long-latency instructions do not block unrelated short-latency instructions. During commit, instructions retire in group order, with all completed instructions in a group eligible for simultaneous retirement once the oldest instruction in the group finishes.

Dynamic Capacity Adjustment

AROB’s size adapts based on workload characteristics. When long-latency instructions dominate, AROB expands to accommodate more short-latency instructions, reducing ROB pressure. Conversely, when short-latency instructions prevail, AROB contracts to conserve power. This flexibility enhances performance across diverse applications.

NA-ROB Processor Architecture

The NA-ROB processor integrates these innovations into a six-stage, dual-issue (2-way) superscalar pipeline:

  1. Fetch (IF): Two instructions are fetched per cycle from the instruction cache.
  2. Decode (ID): Instructions are decoded, and the zero-register strategy classifies them for ROB, AROB, or ZRR allocation.
  3. Issue (IS): Instructions are dispatched to execution units based on operand readiness.
  4. Execute (EX): Operations are performed in ALUs, multipliers, or memory units.
  5. Writeback (WB): Results are written to ROB or AROB entries.
  6. Commit (COM): Instructions retire in program order, with group-based prioritization.

The pipeline supports out-of-order execution while maintaining in-order commit correctness. Key execution units include two ALUs, a multiplier, a load/store unit, and a branch predictor.

Experimental Evaluation

NA-ROB was implemented in Verilog and synthesized on a Xilinx Artix-7 FPGA. Functional validation used the RISC-V test suite, confirming correct operation for all instruction types. Performance was evaluated using SPEC2006 benchmarks, comparing NA-ROB against a traditional ROB design.

Performance Metrics

  1. IPC Improvement: NA-ROB achieved an average IPC of 1.28, a 66% increase over the baseline (0.77). This gain stems from reduced ROB contention and increased parallel instruction execution.
  2. Blocking Probability: The likelihood of ROB stalls decreased by 48%, with some benchmarks showing up to a 64% reduction. AROB’s partitioning effectively mitigated long-latency blocking.
  3. Power Efficiency: At 0.21 mW, NA-ROB consumed less power than traditional designs (0.6 mW) and outperformed other advanced processors like BOOM (1.25 IPC) and Two-tier Retirement (1.23 IPC).

Conclusion

NA-ROB represents a significant advancement in superscalar processor design by optimizing ROB utilization and mitigating long-latency blocking. The zero-register allocation strategy minimizes unnecessary ROB entries, while AROB dynamically partitions instructions to enhance parallelism. These innovations collectively deliver a 66% IPC improvement and 48% lower blocking probability, demonstrating the effectiveness of the approach.

Future work will focus on enhancing security and reliability, ensuring that performance gains do not compromise system integrity. Techniques such as speculative execution hardening and error-correcting mechanisms will be explored to fortify NA-ROB against emerging threats.

doi.org/10.19734/j.issn.1001-3695.2024.06.0236

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