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Out-of-Order Execution

Concept WIKI v4 · 8/3/2026

Out-of-order execution is a processor execution strategy in which instructions are dispatched and completed in an order different from program order. The available evidence describes it as a defining feature of high-performance pipelined RISC and RISC-V cores (e.g., the BOOM core used in the SNAP hardware-fuzzing platform), links it to enlarged processor state spaces that complicate test generation and verification, and notes that the RVVI-TRACE interface explicitly supports out-of-order cores. Two cited implementation directions include a low-power FPGA-based OoO floating-point engine for the Lagarto II core and the energy-efficient CG-OoO coarse-grain out-of-order architecture, which uses block-level scheduling and Skipahead issue to reduce energy use.

Overview

Out-of-order execution is described in the provided evidence as a processor execution strategy used in pipelined, high-performance cores. One cited case study states that the Verified Architecture MicroProcessor (VAMP) is "a pipelined reduced instruction set (RISC) processor based on the out-of-order execution principle." [C1] A second source groups it among "complex performance enhancements" of CPU cores alongside pipelines, multiple instruction issue, and branch prediction. [C2] A third source lists "in-order or out-of-order execution strategies" among the features that make microprocessor verification challenging. [C3]

Use in pipelined RISC processors

The VAMP case study places out-of-order execution in the hardware layer of the Verisoft architecture, specifically at the assembly level called VAMPasm. VAMPasm is described as the instruction set of VAMP, while VAMP itself is characterized as a pipelined RISC processor based on out-of-order execution. [C1]

The same source states that VAMPasm contains 56 instructions, grouped into memory data transfer, constant data transfer, register data transfer, arithmetic and logical operations, test operations, shift operations, control operations, and interrupt handling. [C4]

Effect on processor state space and test-program generation

A formal processor-modeling and test-generation paper ("Generating Test Programs to Cover Pipeline Interactions") explicitly compares in-order and out-of-order pipeline configurations combined with scalar or 2-way superscalar issue. The paper reports the following reachable-state and test-suite statistics from Table 1: [C5]

  • In-order, superscalarity = 1: 42,754 reachable states, 95,086 transitions, 13,232 test programs (average length 16 instructions, generated in 1m30s)
  • In-order, superscalarity = 2: 43,590 reachable states, 124,256 transitions, 15,334 test programs (average length 17 instructions, generated in 1m44s)
  • Out-of-order, superscalarity = 1: 220,039 reachable states, 522,088 transitions, 84,401 test programs (average length 17 instructions, generated in 8m26s)
  • Out-of-order, superscalarity = 2: 310,993 reachable states, 851,041 transitions, 116,260 test programs (average length 20 instructions, generated in 12m24s)

The paper observes that enabling out-of-order execution increases the number of reachable global states and transitions by roughly an order of magnitude relative to the in-order configurations, which in turn drives up the number of test programs needed to cover pipeline interactions. The same paper notes that the number of reachable states and transitions is only a fraction of the total global state space, which is on the order of 10²⁰. [C5]

The test-generation approach described builds executable assembly-level programs by traversing the global finite state machine composed from operation-level and hardware-level extended FSMs, with the ISA specified in MADL and the micro-architecture specified in XML. [C6]

Role in commercial CPU verification practice

A 2015 press release from Test and Verification Solutions (TVS) lists out-of-order execution as one of several complex performance enhancements implemented in modern CPU cores, alongside pipelines, multiple instruction issue, and branch prediction, in addition to memory-access acceleration features such as caching. The release states that these enhancements "can break the functional correctness of the core" and therefore require specialist verification techniques such as constrained-random instruction-stream execution, in which small assembler programs are generated for execution on the core. [C2]

To address this, TVS extended its CPU verification capability with a new Instruction Stream Generation tool called asureISG, initially targeting single-CPU-core verification with planned multi-core support, alongside a new team of CPU verification engineers delivering CPU verification services. The CEO statement highlights that CPU cores are increasingly complex to verify. [C2]

Role in microprocessor verification more broadly

Out-of-order execution is presented as one of several processor features that expand the verification problem. The EETimes constrained-random verification article groups it with complex instruction sets, multiple pipeline stages, instruction parallelism, scalar/vector operations, and other features that create many corner cases, making traditional directed-test creation unreasonable in effort. [C3]

In the VAMP case study, tests are generated from a formal model of the instruction set. The authors describe testing conformance of the gate level, corresponding to the implementation in traditional model-based testing, against the assembly level, corresponding to the model. [C7]

RISC-V microarchitecture context

A RISC-V microarchitecture verification source identifies out-of-order execution as a common high-performance technique, alongside speculative execution. It states that such techniques increase complexity and can expose security vulnerabilities, citing Spectre and Meltdown as examples. [C8]

That same RISC-V source emphasizes that processor verification is not limited to checking that instructions execute correctly; the harder challenges lie in the microarchitecture and pipeline. It also notes that simulation-based verification alone can be inadequate, motivating additional techniques such as formal verification. [C9]

RVVI-TRACE support for out-of-order cores

The RISC-V Verification Interface (RVVI) draft standard defines three interfaces for RISC-V processor design verification. Its core RTL trace interface, RVVI-TRACE (Version 1.7), is described as providing values, state, and events related to the internal signals of a core's micro-architecture to test bench components. The RVVI-TRACE specification explicitly states that the interface includes capabilities for use with "simple single hart in-order cores to multi-hart, multi-issue, Out-of-Order, cores with asynchronous interrupts, and debug modes etc." [C10] The RVVI-TRACE interface is defined in SystemVerilog and additionally allows net changes observed by the RISC-V core to be propagated to consumers of the interface. [C10]

Out-of-order cores as targets for hardware-assisted fuzzing

The SNAP hardware-fuzzing platform is built on top of the BOOM core, described as "the out-of-order BOOM core," and characterized as "one of the most sophisticated open-source RISC-V processors to match commercial ones with modern performance optimizations." [C11] SNAP extends the Fetch Controller with Trace Decision Logic that tags traced instructions using two reserved bits (uses_buq and uses_lbq). [C11]

The same source describes how SNAP's Bitmap Update Queue (BUQ) exploits out-of-order semantics to update a coverage bitmap without stalling the CPU pipeline: the load part of the bitmap update is allowed to proceed speculatively ahead of the corresponding store, while speculative loads are delayed only when an older store to the same bitmap location is pending. Stores themselves are described as being "executed in program order." [C12]

Implementation case studies of out-of-order execution

Lagarto II OoO floating-point engine (FPGA). A thesis describes the design in hardware description languages and implementation in FPGA of an out-of-order execution engine of floating-point arithmetic operations for the Lagarto II core. The first proposal covers a low-power issue queue for out-of-order processors, a register bank, a bypass network, and IEEE-754-conformant functional units for addition/subtraction, multiplication, division/reciprocal, and Fused Multiply Accumulate (FMAC), supporting double-precision format and denormalized numbers. A second proposal is based on a pair of FMAC units that can perform almost all floating-point operations and is reported to be more beneficial in area, performance, and energy efficiency compared with the first version. [C13]

CG-OoO (Coarse-Grain Out-of-Order). A general-purpose processor, CG-OoO, is introduced as aiming to approach In-Order processor energy while maintaining Out-of-Order performance. It speculates, fetches, schedules, and commits code at block-level granularity; eliminates unnecessary accesses to energy-consuming tables; turns large tables into smaller, distributed, cheaper-to-access tables; leverages compiler-level code optimizations for efficient static code; and exploits dynamic instruction-level parallelism and block-level parallelism. CG-OoO introduces a "Skipahead issue" complexity-effective, limited out-of-order instruction scheduling model. The paper reports that the techniques applied at the compiler and processor pipeline stages close 64% of the average energy gap between In-Order and Out-of-Order baseline processors at the performance of the OoO baseline, making CG-OoO 1.9× more efficient than OoO on the energy-delay product inverse metric. [C14]

LINKED ENTITIES

1 links
RVVI-Trace USES

CITATIONS

14 sources
14 citations
[1] VAMP is a pipelined RISC processor based on the out-of-order execution principle. Verisoft VAMP case study (previous article evidence)
[2] Out-of-order execution is listed among complex CPU core performance enhancements that can break functional correctness. TVS asureISG / EETimes constrained-random verification article (previous article evidence)
[3] In-order or out-of-order execution strategies are among features that make microprocessor verification challenging. EETimes constrained-random verification article (previous article evidence)
[4] VAMPasm contains 56 instructions grouped into several categories. Verisoft VAMP case study (previous article evidence)
[5] Enabling out-of-order execution increases reachable states, transitions, and test-program counts by roughly an order of magnitude over in-order configurations. "Generating Test Programs to Cover Pipeline Interactions" Table 1 (previous article evidence)
[6] Test programs are generated by traversing a global FSM composed of operation- and hardware-level extended FSMs; ISA in MADL, micro-architecture in XML. "Generating Test Programs to Cover Pipeline Interactions" (previous article evidence)
[7] VAMP testing verifies conformance of the gate level against the assembly-level formal model. Verisoft VAMP case study (previous article evidence)
[8] Out-of-order and speculative execution are common high-performance RISC-V techniques that increase complexity and can expose security vulnerabilities (Spectre, Meltdown). RISC-V microarchitecture verification source (previous article evidence)
[9] Verification challenges in microarchitecture and pipeline motivate formal verification beyond simulation-based methods. RISC-V microarchitecture verification source (previous article evidence)
[10] RVVI-TRACE (Version 1.7) explicitly supports simple single-hart in-order cores to multi-hart, multi-issue, Out-of-Order cores with asynchronous interrupts and debug modes; it is defined in SystemVerilog and propagates net changes. riscv-verification/RVVI (RVVI GitHub README)
[11] SNAP is built on the out-of-order BOOM core, an open-source RISC-V processor with modern performance optimizations, and adds Trace Decision Logic that tags traced instructions with uses_buq and uses_lbq. Hardware Support to Improve Fuzzing Performance and Precision (SNAP)
[12] SNAP's Bitmap Update Queue exploits out-of-order semantics: loads may proceed speculatively ahead of stores; stores are executed in program order; speculative loads stall only when an older store to the same bitmap location is pending. Hardware Support to Improve Fuzzing Performance and Precision (SNAP)
[13] An FPGA-based out-of-order execution engine of floating-point arithmetic operations for the Lagarto II core includes a low-power issue queue, register bank, bypass network, and IEEE-754-conformant add/sub, mul, div/reciprocal, and FMAC units supporting double-precision and denormals; a second FMAC-pair-based design is reported to improve area, performance, and energy efficiency. Design and implementation of an out-of-order execution engine of floating-point arithmetic operations (arXiv 2111.01948)
[14] CG-OoO achieves close to In-Order energy while maintaining OoO performance via block-level code processing, distributed tables, compiler optimizations, and Skipahead issue; it closes 64% of the average energy gap between In-Order and Out-of-Order baselines at OoO performance and is 1.9× more efficient than OoO on the energy-delay product inverse metric. CG-OoO: Energy-Efficient Coarse-Grain Out-of-Order Execution (arXiv 1606.01607)

VERSION HISTORY

v4 · 8/3/2026 · minimax/minimax-m3 (current)
v3 · 6/16/2026 · minimax/minimax-m3
v2 · 5/28/2026 · gpt-5.5
v1 · 5/26/2026 · gpt-5.5