The numerous emerging implementations of RISC-V processors and frameworks underline the success of this Instruction Set Architecture (ISA) specification. The free and open source character of many implementations facilitates their adoption in academic and commercial projects. As yet it is not easy to say which implementation fits best for a system with given requirements such as processing performance or power consumption. With varying backgrounds and histories, the developed RISC-V processors are very different from each other. Comparisons are difficult, because results are reported for arbitrary technologies and configuration settings. Scaling factors are used to draw comparisons, but this gives only rough estimates. In order to give more substantiated results, this paper compares the most prominent open-source application-class RISC-V projects by running identical benchmarks on identical platforms with defined configuration settings. The Rocket, BOOM, CVA6, and SHAKTI C-Class implementations are evaluated for processing performance, area and resource utilization, power consumption as well as efficiency. Results are presented for the Xilinx Virtex UltraScale+ family and GlobalFoundries 22FDX ASIC technology.

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A comparative survey of open-source application-class RISC-V processor implementations

Vector architectures lack tools for research. Consider the gem5 simulator, which is possibly the leading platform for computer-system architecture research. Unfortunately, gem5 does not have an available distribution that includes a flexible and customizable vector architecture model. In consequence, researchers have to develop their own simulation platform to test their ideas, which consume much research time. However, once the base simulator platform is developed, another question is the following: Which applications should be tested to perform the experiments? The lack of Vectorized Benchmark Suites is another limitation. To face these problems, this work presents a set of tools for designing and evaluating vector architectures. First, the gem5 simulator was extended to support the execution of RISC-V Vector instructions by adding a parameterizable Vector Architecture model for designers to evaluate different approaches according to the target they pursue. Second, a novel Vectorized Benchmark Suite is presented: a collection composed of seven data-parallel applications from different domains that can be classified according to the modules that are stressed in the vector architecture. Finally, a study of the Vectorized Benchmark Suite executing on the gem5-based Vector Architecture model is highlighted. This suite is the first in its category that covers the different possible usage scenarios that may occur within different vector architecture designs such as embedded systems, mainly focused on short vectors, or High-Performance-Computing (HPC), usually designed for large vectors.

https://dl.acm.org/doi/pdf/10.1145/3422667

A RISC-V Simulator and Benchmark Suite for Designing and Evaluating Vector Architectures

Resource-Constrained electronic devices targeting IoT applications need a microcontroller to control their operation, and hence this microcontroller should be energy efficient to increase battery life. One of the emerging open-source processors ISA is RISC-V; as an open-source, it provides a great opportunity for innovation and creativity in designing processor cores. This study targets to survey open-source RISC-V cores and classify them as high-performance and resource-constrained. Afterward, we shortlist the most optimized cores for resource-constrained devices. Seven shortlisted cores are implemented using an ASIC prototyping platform as a unified technology and are compared using resource utilization and energy consumption profile to find the most energy efficient core. We proposed a method to evaluate the energy consumption using power and performance values. Results showed Ibex core to have the best energy consumption characteristics with 8.7 Coremark iterations/mJ over the ASIC prototyping platform.

RISC-V Resource-Constrained Cores: A Survey and Energy Comparison

Vector architectures are gaining traction for highly efficient processing of data-parallel workloads, driven by all major ISAs (RISC-V, Arm, Intel), and boosted by landmark chips, like the Arm SVE-based Fujitsu A64FX, powering the TOP500 leader Fugaku. The RISC-V V extension has recently reached 1.0-Frozen status. Here, we present its first open-source implementation, discuss the new specification's impact on the micro-architecture of a lane-based design, and provide insights on performance-oriented design of coupled scalar-vector processors. Our system achieves comparable/better PPA than state-of-the-art vector engines that implement older RVV versions: 15% better area, 6% improved throughput, and FPU utilization >98.5% on crucial kernels.

A “New Ara” for Vector Computing: An Open Source Highly Efficient RISC-V V 1.0 Vector Processor Design

While research has shown that the agile chip design methodology is promising to sustain the scaling of computing performance in a more efficient way, it is still of limited usage in actual applications due to two major obstacles: 1) Lack of tool-chain and developing framework supporting agile chip design, especially for large-scale modern processors. 2) The conventional verification methods are less agile and become a major bottleneck of the entire process. To tackle both issues, we propose MINJIE, an open-source platform supporting agile processor development flow. MINJIE integrates a broad set of tools for logic design, functional verification, performance modelling, pre-silicon validation and debugging for better development efficiency of state-of-the-art processor designs. We demonstrate the usage and effectiveness of MINJIE by building two generations of an open-source superscalar out-of-order RISC-V processor code-named XIANGSHAN using agile methodologies. We quantify the performance of XIANGSHAN using SPEC CPU2006 benchmarks and demonstrate that XIANGSHAN achieves industry-competitive performance.

Towards Developing High Performance RISC-V Processors Using Agile Methodology

The open source RISC-V ISA has been quickly gaining momentum. This paper presents Xuantie-910, an industry leading 64-bit high performance embedded RISC-V processor from Alibaba T-Head division. It is fully based on the RV64GCV instruction set and it features custom extensions to arithmetic operation, bit manipulation, load and store, TLB and cache operations. It also implements the 0.7.1 stable release of RISC-V vector extension specification for high efficiency vector processing. Xuantie-910 supports multi-core multi-cluster SMP with cache coherence. Each cluster contains 1 to 4 core(s) capable of booting the Linux operating system. Each single core utilizes the state-of-the-art 12-stage deep pipeline, out-of-order, multi-issue superscalar architecture, achieving a maximum clock frequency of 2.5 GHz in the typical process, voltage and temperature condition in a TSMC 12nm FinFET process technology. Each single core with the vector execution unit costs an area of 0.8 mm2 (excluding the L2 cache). The toolchain is enhanced significantly to support the vector extension and custom extensions. Through hardware and toolchain co-optimization, to date Xuantie-910 delivers the highest performance (in terms of IPC, speed, and power efficiency) for a number of industrial control flow and data computing benchmarks, when compared with its predecessors in the RISC-V family. Xuantie-910 FPGA implementation has been deployed in the data centers of Alibaba Cloud, for application-specific acceleration (e.g., blockchain transaction). The ASIC deployment at low-cost SoC applications, such as IoT endpoints and edge computing, is planned to facilitate Alibaba's end-to-end and cloud-to-edge computing infrastructure.

Xuantie-910: A Commercial Multi-Core 12-Stage Pipeline Out-of-Order 64-bit High Performance RISC-V Processor with Vector Extension : Industrial Product

Xuantie-910: Innovating Cloud and Edge Computing by RISC-V

A processor core, a processor, an apparatus, and an instruction processing method are disclosed. The processor core includes: an instruction fetch unit, where the instruction fetch unit includes a speculative execution predictor and the speculative execution predictor compares a program counter of a memory access instruction with a table entry stored in the speculative execution predictor and marks the memory access instruction; a scheduler unit adapted to adjust a send order of marked memory access instructions and send the marked memory access instructions according to the send order; an execution unit adapted to execute the memory access instructions according to the send order. In the instruction fetch unit, a memory access instruction is marked according to a speculative execution prediction result. In the scheduler unit, a send order of memory access instructions is determined according to the marked memory access instruction and the memory access instructions are sent. In the execution unit, the memory access instructions are executed according to the send order. This helps avoiding re-execution of a memory access instruction due to an address correlation of the memory access instruction. Consequently, this eliminates the need of adding an idle cycle in an instruction pipeline and the need of refreshing the pipeline to clear a memory access instruction that is incorrectly speculated.

Lu Yimin

Papers

Xuantie-910: A Commercial Multi-Core 12-Stage Pipeline Out-of-Order 64-bit High Performance RISC-V Processor with Vector Extension : Industrial Product

Xuantie-910: Innovating Cloud and Edge Computing by RISC-V

Speculative execution of correlated memory access instruction methods, apparatuses and systems