A computer-implemented method for processing signals is provided including advantageously generating a temporally continuous weighted pulse position modulation (CW PPM) duration signal from an input analog signal, converting the CW PPM duration signal to a memory access signal, executing a multiply and accumulate (MAC) operation with the memory access signal, and advantageously generating the input analog signal from a result of the MAC operation by an activation function (AF).

The present invention discloses a method for external devices accessing computer memory, which includes: the external device applying to a computer for a memory space with a certain size, and receiving multiple memory blocks fed back by the computer; the external device establishing a memory mapping relation between the external device and the computer by means of a sequential storage structure or a chain storage structure; and when initiating a read-and-write operation, the external device finding the corresponding offset address in said computer according to the memory mapping relation between the external device and the computer, generating a read-and-write burst command, and actualizing read-and-write operations in the computer memory. The present invention can achieve the rapid and continuous access to multiple discontinuous memory areas of the computer memory, and improve the speed in the computer’s operating system and external devices accessing the memory.

A technique is provided for training a prediction apparatus. The apparatus has an input interface for receiving a sequence of training events indicative of program instructions, and identifier value generation circuitry for performing an identifier value generation function to generate, for a given training event received at the input interface, an identifier value for that given training event. The identifier value generation function is arranged such that the generated identifier value is dependent on at least one register referenced by a program instruction indicated by that given training event. Prediction storage is provided with a plurality of training entries, where each training entry is allocated an identifier value as generated by the identifier value generation function, and is used to maintain training data derived from training events having that allocated identifier value. Matching circuitry is then responsive to the given training event to detect whether the prediction storage has a matching training entry (i.e. an entry whose allocated identifier value matches the identifier value for the given training event). If so, it causes the training data in the matching training entry to be updated in dependence on the given training event.

A memory management system includes a cache invalidation logic configured to invalidate, based a cache invalidation event, cache entries within a cache memory by having each cache entry, of the cache entries within the cache memory, reference a respective dummy address from among dummy addresses within a dummy address space, wherein the cache memory is assigned to a memory, the memory has a memory address space associated therewith to provide access the memory, and each dummy address of the dummy addresses within the dummy address space is distinct from any address of the memory address space.

Techniques for computer memory management are disclosed herein. In one embodiment, a method includes in response to receiving a request for allocation of memory, determining whether the request is for allocation from a first memory region or a second memory region of the physical memory. The first memory region has first memory subregions of a first size and the second memory region having second memory subregions of a second size larger than the first size of the first memory region. The method further includes in response to determining that the request for allocation of memory is for allocation from the first or second memory region, allocating a portion of the first or second multiple memory subregions of the first or second memory region, respectively, in response to the request.

Various embodiments set forth techniques for free space management in a block store. The techniques include receiving a request to allocate one or more blocks in a block store, accessing a sparse hierarchical data structure to identify an allocator page identifying a region of a backing store having a greatest number of free blocks, and allocating the one or more blocks.

Systems and methods for performing data protection operations including garbage collection operations and copy forward operations. For deduplicated data stored in a cloud-based storage or in a cloud tier that stores containers containing dead and live segments or dead and live regions such as compression regions, the dead compression regions are deleted by copying the live compression regions into new containers and then deleting the old containers. The copy forward is based on a recipe from a data protection system and is performed using a serverless approach.

Technologies for providing shared memory for accelerator sleds includes an accelerator sled to receive, with a memory controller, a memory access request from an accelerator device to access a region of memory. The request is to identify the region of memory with a logical address. Additionally, the accelerator sled is to determine from a map of logical addresses and associated physical address, the physical address associated with the region of memory. In addition, the accelerator sled is to route the memory access request to a memory device associated with the determined physical address.

A compute instance is instrumented to detect certain kernel memory allocation functions, in particular functions that allocate heap memory and/or make allocated memory executable. Dynamic shell code exploits can then be detected when code executing from heap memory allocates additional heap memory and makes that additional heap memory executable.

Learning-based power modeling of a processor core includes generating, using computer hardware, pipeline snapshot data specifying a plurality of snapshots for a pipeline of a processor core. Each snapshot specifies a state of the pipeline for a clock cycle in executing a computer program over a plurality of clock cycles. A plurality of estimates of power consumption for the processor core in executing the computer program for the plurality of clock cycles are determined, using an instruction-based power model executed by the computer hardware, a based on the pipeline snapshot data. The plurality of estimates of power consumption are calculated using the instruction-based power model based on the plurality of snapshots over the plurality of clock cycles.