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Updated: Jul 27, 2026
No. of Questions: 325 Questions & Answers with Testing Engine
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| Certification Vendor: | Huawei |
| Exam Name: | HCIE-Intelligent Computing V1.0 (Written Exam) |
| Exam Number: | H13-231 |
| Passing Score: | 600 / 1000 |
| Real Exam Qty: | 60 |
| Related Certifications: | HCIE-Intelligent Computing Lab Exam (H13-232) HCIE-Intelligent Computing Interview Exam (H13-233) |
| Exam Format: | Single-choice, Multiple-choice, True/False, Drag-and-drop, Scenario-based questions |
| Available Languages: | English, Chinese |
| Exam Duration: | 90 minutes |
| Certificate Validity Period: | 2 years |
| Exam Price: | USD 300 |
| Recommended Training: | HCIE-Intelligent Computing Official Training |
| Exam Registration: | Huawei Certification Portal Pearson VUE Registration |
| Sample Questions: | Huawei H13-231 Sample Questions |
| Exam Way: | In-person at Pearson VUE authorized centers or online proctored |
| Pre Condition: | No mandatory prerequisites; recommended to have HCIP-level knowledge or 3β5 years of relevant ICT experience |
| Official Syllabus URL: | https://e.huawei.com/en/talent/certification |
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Computing Ecosystem Business Insights | 20% | - Industry trends and development status - Kunpeng and Ascend ecosystem overview - Typical application scenarios and value analysis |
| Topic 2: System Deployment, Tuning and Maintenance | 20% | - Security and compliance management - Installation and deployment procedures - Performance tuning methodology - Monitoring, O&M and fault handling |
| Topic 3: Intelligent Computing Solution Design | 25% | - Requirements analysis and architecture design - Server and hardware configuration - Software stack selection and deployment - High availability and reliability design |
| Topic 4: Key Technologies and Applications | 35% | - Virtualization and container technology - Storage and network integration - Compiler and optimization tools - Kunpeng architecture and processor technology - Ascend AI processor and computing framework |
1. When building a software-defined storage resource pool with a server, software-defined storage products will be selected. Which of the following types of software-defined storage products are generally divided into? (multiple choice)
A) Hyper-converged architecture
B) Out-of-band storage management
C) Distributed storage (block/file object)
D) In-band storage management
2. Which of the following is correct about the characteristics of heterogeneous computing? (Multiple choice)
A) Common heterogeneous systems are CPU+GPU, GPU+FPGA, CPU+ special chip.
B) The purpose of heterogeneous computing is to solve the problem of insufficient CPU computing power.
C) GPU and CPU can work together to form a future computing system. The advantage of heterogeneous computing is computing acceleration and energy saving. Cooperative work can form a heterogeneous computing system. The advantage of heterogeneous computing is computing acceleration and energy saving.
D) Heterogeneous computing is to develop a series of software and hardware standards so that different types of computing devices can share the process and results of computing.
3. Which of the following options is a common RAID type for servers?
A) RAID0/RAID1/RAID3/RAID5/RAID6/RAID10/RAID1E/RAID50/RAID60
B) RAID0/RAID1/RAID3/RAID5/RAID6/RAID10/RAID50/RAID60
C) RAID0/RAID1/RAID5/RAID6/RAID10/RAID50/RAID60
D) RAID0/RAID1/RAID5/RAID6/RAID10/RAID1E/RAID50/RAID60
4. ARM64 processors almost monopolize server CPUs in the mobile market, and gradually align with X86 business cloudification in function, performance and ecology, data center applications with multiple concurrent / horizontal expansion for green computing, and de- X86ization in some regional markets will bring changes to the ARM market. Pattern of opportunity.
A) False
B) True
5. GPU is widely used in the field of machine learning because of its SIMD (Single Instruction Multiple Data) architecture. FPGAs have become popular recently. Which of the following statements about FPGAs and GPUs is correct?
A) GPU has few execution units and can only process instructions in a single thread.
B) GPU sometimes is that if the computer needs to be changed, it can be reassembled.
C) In terms of peak performance, GPU is lower than FPGA.
D) FPGA can program software according to specific application, and its flexibility is much better than GPU.
Solutions:
| Question # 1 Answer: A,B,C | Question # 2 Answer: B,C,D | Question # 3 Answer: C | Question # 4 Answer: A | Question # 5 Answer: D |
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