Civil Rights
Movements, leaders, victories and the continuing fight for equality.
Explore the people, places, events, achievements, struggles and stories that shaped our journey.
Movements, leaders, victories and the continuing fight for equality.
Innovation, patents, science, technology and world-changing contributions.
Pioneers, champions, Negro Leagues, records, activism and excellence.
Meet the people whose lives, choices and achievements shaped the journey.
Black towns, communities, institutions and places where history happened.
Moments that changed communities, movements, institutions and the nation.
Wilmington, North Carolina once had a thriving Black middle class and an elected interracial government. In 1898 white supremacists used violence to overthrow that government, kill Black residents and drive many others from the city.
MORE →Reflects the personal views, recollections, and perspective of the author, Mike Davis.
This is a personal recollection on the Move fire on May 13, 1985
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.[1][2] 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. Prefetching is based on the principle of data locality.
Cache prefetching can either fetch data or instructions into cache.
Cache prefetching can be accomplished either by hardware or by software.[3]

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.[3][12] 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[9][13][14] exploit this property to predict and prefetch for future accesses.
This class of prefetchers looks for memory access streams that repeat over time.[15][16] 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.[17][18]
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.[19] Recent research[20][21] has focused on building collaborative mechanisms to synergistically use multiple prefetching schemes for better prefetching coverage and accuracy.
Compiler-directed prefetching is widely used within loops with a large number of iterations. In this technique, the compiler predicts future cache misses and inserts a prefetch instruction based on the miss penalty and execution time of the instructions.
These prefetches are non-blocking memory operations; that is, these memory accesses do not interfere with actual memory accesses. They do not change the state of the processor or cause page faults.
One main advantage of software prefetching is that it reduces the number of compulsory cache misses.[3]
The following example shows the addition of a prefetch instruction into code to improve cache performance.
In the following iteration,
for (size_t i = 0; i < 1024; ++i) {
array1[i] *= 2;
}
the ith element of the array array1 is accessed. The system can prefetch the elements that are presumably accessed in future iterations by inserting a prefetch instruction as shown below:
for (size_t i = 0; i < 1024; ++i) {
prefetch(array1[i + k]);
array1[i] *= 2;
}
Here, the prefetch stride, k depends on two factors, the cache miss penalty and the time it takes to execute a single iteration of the for-loop. For instance, if one iteration of the loop takes 7 cycles to execute, and the cache miss penalty is 49 cycles, then there should be k = 49/7 = 7 – which means that the system should prefetch 7 elements ahead. With the first iteration, i will be 0, so the system prefetches the 7th element. Now, with this arrangement, the first 7 accesses (i = 0 → 6) will still be misses (under the simplifying assumption that each element of array1 is in a separate cache line of its own).
Cache prefetching may be judged by three main metrics.[3]
Coverage is the fraction of total misses that are eliminated because of prefetching, i.e.
where
Accuracy is the fraction of total prefetches that were useful – that is, the ratio of the number of memory addresses prefetched that were actually referenced by the program to the total prefetches done.
While it appears that having perfect accuracy might imply that there are no misses, this is not the case. The prefetches themselves might result in new misses if the prefetched blocks are placed directly into the cache. Although these may be a small fraction of the total number of misses observed without any prefetching, this is a non-zero number of misses.
The qualitative definition of timeliness is the amount of time elapsed from prefetch to the actual reference. For example: for prefetching to be useful in a for loop where each iteration takes three cycles to execute and the prefetch operation takes twelve cycles, the system must start the prefetch 12/3 = 4 iterations prior to its usage to maintain timeliness.
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Source: Wikipedia. Article content is retrieved live through the MediaWiki API.
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. Prefetching is based on the principle of data locality.
In computing, a cache ( KASH) is a hardware or software component that stores data so that future requests for that data can be served faster; the data stored in a cache might be the result of an earlier computation or a copy of data stored elsewhere. A cache hit occurs when the requested data can be found in a cache, while a cache miss occurs when it cannot. Cache hits are served by reading data from the cache, which is faster than recomputing a result or reading from a slower data store; thus, the more requests that can be served from the cache, the faster the system performs. To be cost-effective, caches must be relatively small. Nevertheless, caches are effective in many areas of computing because typical computer applications access data with a high degree of locality of reference. Such access patterns exhibit temporal locality, where data that has been recently requested is requested again, and spatial locality, where data is requested that is stored near data that has already been requested.
A CPU cache is a hardware cache used by the central processing unit (CPU) of a computer to reduce the average cost (time or energy) to access data from the main memory. A cache is a smaller, faster memory, located closer to a processor core, which stores copies of the data from frequently used main memory locations, avoiding the need to always refer to main memory which may be tens to hundreds of times slower to access. Cache memory is typically implemented with static random-access memory (SRAM), which requires multiple transistors to store a single bit. This makes it expensive in terms of the area it takes up, and in modern CPUs the cache is typically the largest part by chip area. The size of the cache needs to be balanced with the general desire for smaller chips which cost less. Some modern designs implement some or all of their cache using the physically smaller eDRAM, which is slower to use than SRAM but allows larger amounts of cache for any given amount of chip area. Most CPUs have a hierarchy of multiple cache levels (L1, L2, often L3, and rarely even L4), with separate instruction-specific (I-cache) and data-specific (D-cache) caches at level 1. The different levels are implemented in different areas of the chip; L1 is located as close to a CPU core as possible and thus offers the highest speed due to short signal paths, but requires careful design. L2 caches are physically separate from the CPU and operate slower, but place fewer demands on the chip designer and can be made much larger without impacting the CPU design. L3 caches are generally shared among multiple CPU cores. Other types of caches exist (that are not counted towards the "cache size" of the most important caches mentioned above), such as the translation lookaside buffer (TLB) which is part of the memory management unit (MMU) which most CPUs have. Input/output sections also often contain data buffers that serve a similar purpose.
In computing, cache replacement policies (also known as cache replacement algorithms or cache algorithms) are optimizing instructions or algorithms which a computer program or hardware-maintained structure can utilize to manage a cache of information. Caching improves performance by keeping recent or often-used data items in memory locations which are faster, or computationally cheaper to access, than normal memory stores. When the cache is full, the algorithm must choose which items to discard to make room for new data.
Before the 1921 destruction of Tulsa’s Greenwood District, Black residents had created a remarkable center of business and community life. The district included stores, professional offices, entertainment venues and homes owned by Black citizens. Understanding Greenwood means learning what was built—not only what was burned.
MORE →Mae Jemison, aboard Space Shuttle Endeavour in 1992.