Memory: Foundations And Applicat
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The McKnight Brain Research Foundation (MBRF) and the American Federation for Aging Research (AFAR) will provide up to two 3-year awards of $750,000 (USD) each to advanced Assistant Professors and recently appointed Associate Professors (MDs and PhDs.) One award will be made to support studies focusing on clinical translational research and another award toward understanding basic biological mechanisms underlying cognitive aging and age-related memory loss. The application deadline is August 1, 2022.
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N2 - Software Transactional Memory algorithms associate metadata with the memory locations accessed during a transactions lifetime. This metadata may be stored in an external table and accessed by way of a function that maps the address of each memory location with the table entry that keeps its metadata (this is the out-place or external scheme); or alternatively may be stored adjacent to the associated memory cell by wrapping them together (the in-place scheme). In transactional memory multi-version algorithms, several versions of the same memory location may exist. The efficient implementation of these algorithms requires a one-to-one correspondence between each memory location and its list of past versions, which is stored as metadata. In this chapter we address the matter of the efficient implementation of multi-version algorithms in Java by proposing and evaluating a novel in-place metadata scheme for the Deuce framework. This new scheme is based in Java Bytecode transformation techniques and its use requires no changes to the application code. Experimentation indicates that multi-versioning STM algorithms implemented using our new in-place scheme are in average 6 $ faster than when implemented with the out-place scheme.
AB - Software Transactional Memory algorithms associate metadata with the memory locations accessed during a transactions lifetime. This metadata may be stored in an external table and accessed by way of a function that maps the address of each memory location with the table entry that keeps its metadata (this is the out-place or external scheme); or alternatively may be stored adjacent to the associated memory cell by wrapping them together (the in-place scheme). In transactional memory multi-version algorithms, several versions of the same memory location may exist. The efficient implementation of these algorithms requires a one-to-one correspondence between each memory location and its list of past versions, which is stored as metadata. In this chapter we address the matter of the efficient implementation of multi-version algorithms in Java by proposing and evaluating a novel in-place metadata scheme for the Deuce framework. This new scheme is based in Java Bytecode transformation techniques and its use requires no changes to the application code. Experimentation indicates that multi-versioning STM algorithms implemented using our new in-place scheme are in average 6 $ faster than when implemented with the out-place scheme.
A memory leak is an unintentional form of memory consumption whereby the developer fails to free an allocated block of memory when no longer needed. The consequences of such an issue depend on the application itself. Consider the following general three cases:
Avoiding memory leaks in applications is difficult for even the most skilled developers. Luckily, there are tools with aide in tracking down such memory leaks. One such example on the Unix/Linux environment is Valgrind. Valgrind runs the desired program in an environment such that all memory allocation and de-allocation routines are checked. At the end of program execution, Valgrind will display the results in an easy to read manner. The following is the output of Valgrind using the flawed code above:
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4-gigabyte tuning (4GT), also known as application memory tuning, or the /3GB switch, is a technology (only applicable to 32 bit systems) that alters the amount of virtual address space available to user mode applications. Enabling this technology reduces the overall size of the system virtual address space and therefore system resource maximums. For more information, see What is 4GT.
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That puts the datacenter in a quandary, given that the value of modern applications derives from the fact that they can easily share data and the results of processing that data. Cyber security has been a concern since the first moment two computers were networked together. But it moved into the big league with the commercialization of the Internet and shortly thereafter, the emergence of web applications.
With the addition of memory encryption and enclaves, it is now possible to actually deliver a Confidential Computing platform with a TEE that provides data confidentiality. This not only stops unauthorized entities, either people or applications, from viewing data while it is in use, in transit, or at rest. It also stops them from adding, removing, or altering data or code while it is in use, in transit, or at rest too.
It effectively allows enterprises in regulated industries (banking, insurance, finance, healthcare, life sciences for example) as well as government agencies (particularly defense and national security) and multi-tenant cloud service providers to better secure their environments. Importantly, Confidential Computing means that any organization running applications on the cloud can be sure that any other users of the cloud capacity and even the cloud service providers themselves cannot access the data or applications residing within a memory enclave.
The Morris water maze (MWM) was described 20 years ago as a device to investigate spatial learning and memory in laboratory rats. In the meanwhile, it has become one of the most frequently used laboratory tools in behavioral neuroscience. Many methodological variations of the MWM task have been and are being used by research groups in many different applications. However, researchers have become increasingly aware that MWM performance is influenced by factors such as apparatus or training procedure as well as by the characteristics of the experimental animals (sex, species/strain, age, nutritional state, exposure to stress or infection). Lesions in distinct brain regions like hippocampus, striatum, basal forebrain, cerebellum and cerebral cortex were shown to impair MWM performance, but disconnecting rather than destroying brain regions relevant for spatial learning may impair MWM performance as well. Spatial learning in general and MWM performance in particular appear to depend upon the coordinated action of different brain regions and neurotransmitter systems constituting a functionally integrated neural network. Finally, the MWM task has often been used in the validation of rodent models for neurocognitive disorders and the evaluation of possible neurocognitive treatments. Through its many applications, MWM testing gained a position at the very core of contemporary neuroscience research.
Red Hat Runtimes is a set of products, tools, and components for developing and maintaining cloud-native applications. It offers lightweight runtimes and frameworks (like Quarkus) for highly-distributed cloud architectures, such as microservices. 2b1af7f3a8