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Start learning 50% faster. Sign in nowCache memory is a small, high-speed storage located close to or within the CPU. Its primary purpose is to temporarily store frequently accessed data and instructions, reducing the time it takes for the CPU to access main memory. • Why cache memory is critical: Cache bridges the speed gap between the CPU and slower memory systems. By storing copies of frequently used data, it minimizes latency and enhances processing efficiency. The use of cache levels (L1, L2, and L3) ensures optimal performance for different workloads. For example, when a CPU processes a loop in a program, the loop instructions are repeatedly fetched. Without cache, the CPU would access the slower main memory every time, slowing down execution. ________________________________________ Why Other Options Are Incorrect: 1. Backup storage for the main memory: Cache is temporary and volatile, unlike backup storage, which is typically non-volatile. 2. Permanent data storage: Cache memory is volatile and cannot retain data after the system is powered off. 3. Facilitates communication between CPUs: Inter-CPU communication is handled by shared memory or interconnects like buses, not by cache memory. 4. Exclusive for storing user-defined variables: Cache stores both program instructions and data, not just user-defined variables.
In the context of data analysis, which of the following best describes trend analysis?
Which of the following query will return the third-highest salary from an Employee table in SQL?
Which of the following forecasting methods would be most suitable for a time series that exhibits both a long-term trend and seasonality?
Which of the following statements best explains why stratified sampling is preferred over simple random sampling in certain scenarios?
Which of the following statements best describes the role of data visualization in data analysis?
What is the primary difference between Type 1 and Type 2 hypervisors?
Why is sampling often preferred over using the entire population for data analysis?
In time series forecasting, which method combines the concepts of autoregression and moving averages with differencing to make non-stationary data stati...
What is a key difference between random sampling and non-random sampling?
Which natural language processing (NLP) technique is best suited for understanding the contextual meaning of words in a sentence?