Amazon Computer Architecture Interview: Parallelism, Memory
Question Description
What this question covers
This Computer Architecture CS foundation set focuses on how modern processors and systems achieve performance and efficiency. You will be asked to explain and reason about parallel computing, pipelining, caches and the memory hierarchy, and virtual memory mechanisms. Expect conceptual questions that probe correctness and performance trade-offs, not just definitions.
Typical flow in an interview
You may start with short conceptual prompts (e.g., explain pipeline hazards or cache locality), move to whiteboard design or analysis (e.g., show how forwarding and branch prediction reduce stalls), and finish with a problem that requires quantitative reasoning (calculate speedup using Amdahl's law, estimate hit/miss penalties, or design a simple cache replacement policy). Interviewers will frequently follow up with variations that change workload, core count, or memory parameters.
Skills and signals to demonstrate
Show that you can reason about synchronization and correctness in parallel algorithms, identify and mitigate pipeline hazards (data, control, structural), analyze cache behavior and replacement policies (LRU, LFU, write-back vs write-through), explain TLBs and multi-level page tables, and compare ISA and processor types (RISC vs CISC, CPU vs GPU) for latency, throughput, and power. Use concrete examples and back up claims with simple cost models (cycles, IPC, hit/miss rates) to make your answers credible.
Practice problems that combine analysis and trade-offs will help you convert conceptual knowledge into interview-ready explanations.
Common Follow-up Questions
- •Given a 5-stage pipeline, show how forwarding and hazard detection reduce stalls; how would branch prediction change your analysis?
- •Design a cache hierarchy for a throughput-oriented workload; choose sizes, associativity, and replacement policy and justify trade-offs
- •Explain how a TLB interacts with multi-level page tables; how would you estimate TLB pressure and reduce page-walk overhead?
- •Compare implementing a compute kernel on CPU versus GPU: when does Amdahl's law limit speedup and how do memory-bandwidth constraints change the outcome
- •Given a parallel algorithm, measure and explain differences between strong scaling and weak scaling and how synchronization costs affect scalability
Related Questions
Explore More Questions
Practice This Question with AI
Get real-time hints, detailed requirements, and insightful analysis of the question.