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Cache prefetching
Cache prefetching is a technique used by central processing units (CPUs) to boost execution performance by fetching instructions or data from their primary or main storage in slower memory to a faster local memory before it is actually needed. Most modern CPUs have fast and local cache memory in which prefetched data is held until it is required. The source for the prefetch operation is usually main memory. Because of their design, accessing cache memories is typically much faster than accessing main memory. Prefetching can be done with non-blocking cache control instructions.
Cache prefetching can either fetch data or instructions into cache.
Cache prefetching can be accomplished either by hardware or by software.
This type of prefetching monitors the delta between the addresses of the memory accesses and looks for patterns within it.
In this pattern, consecutive memory accesses are made to blocks that are s addresses apart. In this case, the prefetcher calculates the s and uses it to compute the memory address for prefetching. For example, if s = 4, the address to be prefetched would A+4.
In this case, the delta between the addresses of consecutive memory accesses is variable but still follows a pattern. Some prefetcher designs exploit this property to predict and prefetch for future accesses.
This class of prefetchers looks for memory access streams that repeat over time. For example, in the stream of memory accesses N, A, B, C, E, G, H, A, B, C, I, J, K, A, B, C, L, M, N, O, A, B, C, ...; the stream A, B, C is repeating over time. Other design variations have tried to provide more efficient implementations.
Computer applications generate a variety of access patterns. The processor and memory subsystem architectures used to execute these applications further disambiguate the memory access patterns they generate. Hence, the effectiveness and efficiency of prefetching schemes often depends on the application and the architectures used to execute them. Recent research has focused on building collaborative mechanisms to synergistically use multiple prefetching schemes for better prefetching coverage and accuracy.
Hub AI
Cache prefetching AI simulator
(@Cache prefetching_simulator)
Cache prefetching
Cache prefetching is a technique used by central processing units (CPUs) to boost execution performance by fetching instructions or data from their primary or main storage in slower memory to a faster local memory before it is actually needed. Most modern CPUs have fast and local cache memory in which prefetched data is held until it is required. The source for the prefetch operation is usually main memory. Because of their design, accessing cache memories is typically much faster than accessing main memory. Prefetching can be done with non-blocking cache control instructions.
Cache prefetching can either fetch data or instructions into cache.
Cache prefetching can be accomplished either by hardware or by software.
This type of prefetching monitors the delta between the addresses of the memory accesses and looks for patterns within it.
In this pattern, consecutive memory accesses are made to blocks that are s addresses apart. In this case, the prefetcher calculates the s and uses it to compute the memory address for prefetching. For example, if s = 4, the address to be prefetched would A+4.
In this case, the delta between the addresses of consecutive memory accesses is variable but still follows a pattern. Some prefetcher designs exploit this property to predict and prefetch for future accesses.
This class of prefetchers looks for memory access streams that repeat over time. For example, in the stream of memory accesses N, A, B, C, E, G, H, A, B, C, I, J, K, A, B, C, L, M, N, O, A, B, C, ...; the stream A, B, C is repeating over time. Other design variations have tried to provide more efficient implementations.
Computer applications generate a variety of access patterns. The processor and memory subsystem architectures used to execute these applications further disambiguate the memory access patterns they generate. Hence, the effectiveness and efficiency of prefetching schemes often depends on the application and the architectures used to execute them. Recent research has focused on building collaborative mechanisms to synergistically use multiple prefetching schemes for better prefetching coverage and accuracy.