AI Practitioner

I n modern computing, performance is critical. Two major parallel processing models that power today's high-performance computing systems are SIMD (Single Instruction, Multiple Data) and MIMD (Multiple Instruction, Multiple Data). Understanding these models enables engineers to optimize algorithms and leverage hardware capabilities effectively. SIMD: Single Instruction, Multiple Data Concept SIMD is a parallel computing model where a single operation is applied simultaneously to multiple data points. It is highly efficient for data-parallel tasks such as image processing, signal processing, and linear algebra operations. Illustration SIMD Example: Vector Addition A = [1, 2, 3, 4] B = [5, 6, 7, 8] C = A + B (Element-wise) Processor SIMD Unit: Step 1: ADD 1+5 | 2+6 | 3+7 | 4+8 => [6, 8, 10, 12] All operations are executed in lockstep using specialized vector registers (e.g., SSE, AVX on x86 CPUs). Python Support for SIMD Python can leverage SIMD via libraries lik...