PCLMULQDQ (not supported)
E637387
PCLMULQDQ (not supported) refers to the absence of hardware support for the PCLMULQDQ carry-less multiplication instruction, which is used to accelerate certain cryptographic and polynomial arithmetic operations.
All labels observed (2)
| Label | Occurrences |
|---|---|
| PCLMULQDQ | 2 |
| PCLMULQDQ (not supported) canonical | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T7032645 — resolving that mention is where its identity was fixed. The disambiguator weighed these candidate entities and picked the highlighted one (or “None”, minting a new entity). This is how homonymy is resolved: the same surface form can point to different entities.
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: PCLMULQDQ (not supported) Context triple: [Bonnell, supports, PCLMULQDQ (not supported)]
-
A.
Intel AVX2
Intel AVX2 is an x86 instruction set extension from Intel that enhances performance for integer-heavy and vectorized workloads through wider SIMD operations and new vector instructions.
-
B.
Intel AES-NI
Intel AES-NI is a set of hardware instructions introduced by Intel to accelerate and secure AES encryption and decryption operations in modern processors.
-
C.
Intel AVX
Intel AVX is an x86 processor instruction set extension from Intel that accelerates floating-point and vector-intensive workloads, commonly used in high-performance computing, multimedia, and scientific applications.
-
D.
AMD-V
AMD-V is AMD’s hardware-assisted virtualization technology that enables efficient and secure running of virtual machines on compatible processors.
-
E.
P (packed-SIMD extension)
P (packed-SIMD extension) is a RISC-V instruction set extension that adds packed single-instruction multiple-data operations to accelerate parallel data processing tasks such as signal processing and multimedia workloads.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: PCLMULQDQ (not supported) Target entity description: PCLMULQDQ (not supported) refers to the absence of hardware support for the PCLMULQDQ carry-less multiplication instruction, which is used to accelerate certain cryptographic and polynomial arithmetic operations.
-
A.
Intel AVX2
Intel AVX2 is an x86 instruction set extension from Intel that enhances performance for integer-heavy and vectorized workloads through wider SIMD operations and new vector instructions.
-
B.
Intel AES-NI
Intel AES-NI is a set of hardware instructions introduced by Intel to accelerate and secure AES encryption and decryption operations in modern processors.
-
C.
Intel AVX
Intel AVX is an x86 processor instruction set extension from Intel that accelerates floating-point and vector-intensive workloads, commonly used in high-performance computing, multimedia, and scientific applications.
-
D.
AMD-V
AMD-V is AMD’s hardware-assisted virtualization technology that enables efficient and secure running of virtual machines on compatible processors.
-
E.
P (packed-SIMD extension)
P (packed-SIMD extension) is a RISC-V instruction set extension that adds packed single-instruction multiple-data operations to accelerate parallel data processing tasks such as signal processing and multimedia workloads.
- F. None of above. chosen
Statements (25)
| Predicate | Object |
|---|---|
| instanceOf | hardware feature status ⓘ |
| affects |
hardware acceleration of cryptographic operations
ⓘ
hardware acceleration of polynomial arithmetic operations ⓘ |
| appliesTo | CPU or processor ⓘ |
| contrastsWith | PCLMULQDQ (supported) ⓘ |
| describes | CPU feature flag state indicating PCLMULQDQ bit is not set ⓘ |
| hasConsequence |
fallback to generic or scalar implementations
ⓘ
inability to use certain optimized code paths ⓘ |
| hasImpactOn |
latency of polynomial-based algorithms
ⓘ
throughput of certain hash functions ⓘ throughput of certain message authentication codes (MACs) ⓘ |
| implies |
carry-less multiplication must be done in software
ⓘ
reduced performance for algorithms optimized for PCLMULQDQ ⓘ |
| indicates | processor does not implement carry-less multiplication instruction PCLMULQDQ ⓘ |
| mayBeReportedBy |
cryptographic library self-tests
ⓘ
operating system CPU feature enumeration ⓘ virtualization or hypervisor feature masks ⓘ |
| refersTo | absence of support for the PCLMULQDQ instruction ⓘ |
| relatedTo | PCLMULQDQ instruction ⓘ |
| relevantFor |
CRC computation performance
ⓘ
GF(2^n) polynomial multiplication performance ⓘ Galois/Counter Mode (GCM) performance ⓘ |
| usedInContextOf |
CPU feature detection
ⓘ
cryptographic library configuration ⓘ runtime capability checks ⓘ |
How these facts were elicited
The pipeline generated the facts above by prompting gpt-5.1 with this entity's name + description and the instruction below.
Instruction
You are a knowledge base construction expert. Given a subject entity and a description of it, return factual statements that you know for the subject as a JSON list of dictionaries(triples), where keys must be "subject", "predicate" and "object". The number of facts may be very high, between 25 to 50 or more, for very popular subjects. For less popular subjects, the number of facts can be very low, like 5 or 10. # Requirements - If you don't know the subject at all, return an empty list. - If the subject is not a named entity, return an empty list. - Include at least one triple where predicate is "instanceOf". - Do not get too wordy. - Separate several objects into multiple triples with one object.
Input
Subject: PCLMULQDQ (not supported) Description of subject: PCLMULQDQ (not supported) refers to the absence of hardware support for the PCLMULQDQ carry-less multiplication instruction, which is used to accelerate certain cryptographic and polynomial arithmetic operations.
Referenced by (3)
Full triples — surface form annotated when it differs from this entity's canonical label.
linked to: PCLMULQDQ (not supported)
linked to: PCLMULQDQ (not supported)