Statements (149)
| Predicate | Object |
|---|---|
| gptkbp:instance_of |
gptkb:architecture
|
| gptkbp:applies_to |
vector processing
|
| gptkbp:can |
multiple data points
multiple data points simultaneously |
| gptkbp:can_be_combined_with |
gptkb:SIMT
|
| gptkbp:can_be_found_in |
instruction set architectures
|
| gptkbp:can_be_used_for |
batch processing
|
| gptkbp:challenges |
branching operations
|
| gptkbp:describes |
gptkb:Single_Instruction,_Multiple_Data
|
| gptkbp:enables |
data-level parallelism
vectorization of operations |
| gptkbp:enhances |
energy efficiency
algorithm efficiency machine performance data throughput video encoding and decoding |
| gptkbp:has_limitations |
data dependencies
|
| https://www.w3.org/2000/01/rdf-schema#label |
SIMD
|
| gptkbp:improves |
gptkb:performance
performance of data processing |
| gptkbp:is_adopted_by |
gptkb:cloud_computing
machine vision systems automated trading systems |
| gptkbp:is_applied_in |
matrix operations
vector operations |
| gptkbp:is_beneficial_for |
audio processing
financial modeling high-performance computing image manipulation large data sets natural language processing machine learning tasks |
| gptkbp:is_common_in |
gptkb:video_games
gptkb:mobile_devices gptkb:cloud_computing embedded systems gaming consoles high-performance computing scientific computing high-definition video processing |
| gptkbp:is_effective_against |
large-scale data analysis
numerical simulations data compression algorithms |
| gptkbp:is_enhanced_by |
compiler optimizations
|
| gptkbp:is_essential_for |
3 D graphics rendering
|
| gptkbp:is_found_in |
modern CPUs
|
| gptkbp:is_implemented_in |
gptkb:Power_PC_architecture
gptkb:x86_architecture gptkb:ARM_architecture CPUs GPUs AI model training modern CPUs FPGA (Field-Programmable Gate Array) real-time data processing systems graphics processing units (GPUs) vector registers vector instructions SIMD extensions (e.g., SSE, AVX) |
| gptkbp:is_incorporated_in |
AI accelerators
|
| gptkbp:is_optimized_for |
specific algorithms
specific workloads |
| gptkbp:is_part_of |
gptkb:architecture
embedded systems real-time systems modern processors deep learning frameworks high-level programming languages vector processing data parallelism multicore processors signal processing systems high-performance graphics AI frameworks data processing pipelines audio processing systems computer vision systems data analytics frameworks high-performance computing (HPC) image processing systems data analysis frameworks high-performance algorithms multimedia instruction sets parallel computing frameworks |
| gptkbp:is_related_to |
gptkb:AVX
gptkb:SSE data parallelism multicore processors SIMD instructions parallel algorithms multi-threading techniques thread-level parallelism SIMT (Single Instruction, Multiple Threads) |
| gptkbp:is_supported_by |
gptkb:NVIDIA
gptkb:FPGA various programming languages parallel programming models programming languages like C and C++ |
| gptkbp:is_used_by |
gptkb:machine_learning
image processing multimedia applications scientific computing |
| gptkbp:is_used_for |
signal processing algorithms
image recognition tasks |
| gptkbp:is_used_in |
gptkb:crypt
gptkb:virtual_reality gptkb:Telecommunications gptkb:machine_learning gptkb:robotics image processing audio processing augmented reality computer vision deep learning financial modeling image recognition natural language processing real-time processing scientific computing data mining signal processing big data analytics data compression video encoding graphics processing biomedical applications weather simulations machine vision real-time graphics applications network processing 3 D rendering 3 D graphics rendering digital signal processing (DSP) |
| gptkbp:is_utilized_for |
data mining
scientific simulations |
| gptkbp:is_utilized_in |
image processing
real-time processing machine learning frameworks computer vision tasks |
| gptkbp:key |
high throughput
real-time processing applications efficient algorithm design enhanced computational efficiency |
| gptkbp:reduces |
instruction overhead
|
| gptkbp:supports |
data parallelism
data-level parallelism |
| gptkbp:used_in |
parallel processing
|
| gptkbp:bfsParent |
gptkb:Web_Assembly
|
| gptkbp:bfsLayer |
4
|