Intel Corporation

Meta Platforms, Inc.

Facebook, Inc.

Amin Firoozshahian

Omid Azizi

Chandan Egbert

Mahesh Srinivasa Maddury

Mahesh Madhav

Andreas Kleen

Martin Schatz

Alexandre Y Solomatnikov

Abdulkadir Utku Diril

Krishnakumar Narayanan Nair

Olivia Wu

Ehsan Khish Ardestani Zadeh

Thomas Mark Ulrich

Yuchen Hao

Rakesh Komuravelli

Anup Ramesh Kadkol

David R Cheriton

Ashok Raj

Stephen R Van Doren

David Hansen

Eric Gouldey

John Peter Stevenson

Francesc Guim Bernat

David M Durham

Kshitij Arun Doshi

Ravi L Sahita

Mohan J Kumar

Karthik Kumar

Rajesh M Sankaran

Baiju V Patel

Thomas Willhalm

Ravishankar Iyer

Michael Lemay

Andrew J Herdrich

Sara S Baghsorkhi

Jr-Shian Tsai

Vadim Sukhomlinov

Alexander Bachmutsky

Mingqiu Sun

Ian M Steiner

Vedaraman Geetha

Rupin H Vakharwala

Jeffrey D Chamberlain

Eric Dahlen

Nilesh K Jain

Mohammad R Haghighat

Toby Opferman

Mingwei Zhang

Henk G Neefs

Yeluri Raghuram

Dmitry Babokin

Krishna Bhuyan

Mustafa Hajeer

Anil Rao

Leeor Peled

Vijay Bahirji

Areg Melik-Adamyan

Harshad S Sane

Teck Joo Goh

Anup Mohan

Michael Prinke

Wenyong Huang

Mahesh Maddury

Embodiments of systems, apparatuses and methods provide enhanced function as a service (FaaS) to users, e.g., computer developers and cloud service providers (CSPs). A computing system configured to provide such enhanced FaaS service include one or more controls architectural subsystems, software and orchestration subsystems, network and storage subsystems, and security subsystems. The computing system executes functions in response to events triggered by the users in an execution environment provided by the architectural subsystems, which represent an abstraction of execution management and shield the users from the burden of managing the execution. The software and orchestration subsystems allocate computing resources for the function execution by intelligently spinning up and down containers for function code with decreased instantiation latency and increased execution scalability while maintaining secured execution. Furthermore, the computing system enables customers to pay only when their code gets executed with a granular billing down to millisecond increments.

Function as a service (FaaS) system enhancements

Various systems and methods for computer memory overcommitment management are described herein. A system for computer memory management includes a memory device to store data and a mapping table; and a memory overcommitment circuitry to: receive a signal to move data in a first block from a memory reduction area in the memory device to a non-memory reduction area in the memory device, the memory reduction area to store data using a memory reduction technique, and the non-memory reduction area to store data without any memory reduction techniques; allocate a second block in the non-memory reduction area; copy the data in the first block to the second block; and update the mapping table to revise a pointer to point to the second block, the mapping table used to store pointers to memory device in the memory reduction area and the non-memory reduction area.

Reservation architecture for overcommitted memory

A processor system comprises a plurality of processing elements. Each processing element includes a corresponding convolution processor unit configured to perform a portion of a groupwise convolution. The corresponding convolution processor unit determines multiplication results by multiplying each data element of a portion of data elements in a convolution data matrix with a corresponding data element in a corresponding groupwise convolution weight matrix. The portion of data elements in the convolution data matrix that are multiplied belong to different channels and different groups. For each specific channel of the different channels, the corresponding convolution processor unit sums together at least some of the multiplication results belonging to the same specific channel to determine a corresponding channel convolution result data element. The processing elements sum together a portion of the channel convolution result data elements from a group of different convolution processor units to determine a groupwise convolution result data element.

Grouped convolution using point-to-point connected channel convolution engines

A processor system comprises a first and second group of registers and a hardware channel convolution processor unit. The first group of registers is configured to store data elements of channels of a portion of a convolution data matrix. Each register stores at least one data element from each channel. The second group of registers is configured to store data elements of convolution weight matrices including a separate convolution weight matrix for each channel. Each register stores at least one data element from each convolution weight matrix. The hardware channel convolution processor unit is configured to multiply each data element in the first group of registers with a corresponding data element in the second group of registers and sum together the multiplication results for each specific channel to determine corresponding channel convolution result data elements in a corresponding channel convolution result matrix.

Mapping convolution to a channel convolution engine

A processor system comprises two groups of registers and a hardware channel convolution processor unit. The first group of registers is configured to store data elements of channels of a portion of a convolution data matrix. Each register stores at least one data element from each channel. The second group of registers is configured to store data elements of convolution weight matrices including a separate matrix for each channel. Each register stores at least one data element from each matrix. The hardware channel convolution processor unit is configured to multiply each data element in a first and second portion of the first group of registers with a corresponding data element in the second group of registers to determine corresponding multiplication results and sum together the multiplication results for each specific channel to determine two corresponding channel convolution result data elements in a corresponding channel convolution result matrix.

Mapping convolution to a partition channel convolution engine

A processor system comprises a hardware channel convolution processor unit and dot product processor unit. The channel convolution processor unit is configured to perform depthwise convolution, including by multiplying each data element of a first group of data elements of a convolution data matrix with a corresponding data element of a second group of data elements of a plurality of depthwise convolution weight matrices and summing together, for each specific channel, multiplication results corresponding to the specific channel to determine one corresponding result data element in a corresponding channel convolution result matrix to calculate a portion of depthwise convolution results. The dot product processor unit is configured to perform pointwise convolution, including applying pointwise weight matrices to the portion of depthwise convolution results to determine a portion of separable convolution results while at least another portion of the depthwise convolution results is being calculated by the processor system.

Pipelined pointwise convolution using per-channel convolution operations

Processing circuitry for computer memory management includes memory reduction circuitry to implement a memory reduction technique; and reference count information collection circuitry to: access a memory region, the memory region subject to the memory reduction technique; obtain an indication of memory reduction of the memory region; calculate metrics based on the indication of memory reduction of cache lines associated with the memory region; and provide the metrics to a system software component for use in memory management mechanisms.

Hardware-assisted paging mechanisms

A processing device includes a core to execute instructions, and memory management circuitry coupled to, memory, the core and an I/O device that supports page faults. The memory management circuitry includes an express invalidations circuitry, and a page translation permission circuitry. The memory management circuitry is to, while the core is executing the instructions, receive a command to pause communication between the I/O device and the memory. In response to receiving the command to pause the communication, modify permissions of page translations by the page translation permission circuitry and transmit an invalidation request, by the express invalidations circuitry to the I/O device, to cause cached page translations in the I/O device to be invalidated.

Pause communication from I/O devices supporting page faults

Examples relate to an approximative memory deduplication method, a controller apparatus or controller device for a memory or storage controller, a memory or storage controller, a computer system and to a computer program. The approximative memory deduplication method comprises determining a hash value of a data block. The hash value is based on a user-defined approximative hashing function. The approximative memory deduplication method comprises storing a quantized version of the data block based on the hash value using a memory or storage device of the computer system.

Concept for approximate deduplication in storage and memory

A specification of an operation to perform one or more element-wise sums of specified portions of a matrix is received. The specification of the operation is analyzed to select a type of processing load partitioning to be applied. Based on the selected type of processing load partitioning to be applied, processing required to perform the operation is partitioned across a plurality of physical processing elements in parallel. The partitioned processing is distributed to the physical hardware processing elements to perform in parallel the element-wise sums of the specified portions of the matrix.

Distributed physical processing of matrix sum operation

Various systems and methods for computer memory management are described herein. A system for computer memory management includes a first memory device including a mapping table; a second memory device including a staging area; a third memory device including a dedup data region; and a controller operable to: receive a memory access request, the memory access request including an address and data; write the data to the staging area; and update the mapping table with the address.

Lazy memory deduplication

A system for computer memory management that implements a memory pool table, the memory pool table including entries that describe a plurality of memory pools, each memory pool representing a group of memory pages related by common attributes; a per-page tracking table, each entry in the per-page tracking table used to related a memory page with a memory pool of the memory pool table; and processing circuitry to: scan each entry in the per-page tracking table and, for each entry: determine an amount of memory released if the memory page related with the entry is swapped; aggregate the amount of memory for the respective memory pool related with the memory page related with the entry in the per-page tracking table, to produce a per-pool memory aggregate; and output the per-pool memory aggregate for the memory pools related with the memory pages in the per-page tracking table.

Physical page tracking for handling overcommitted memory

Various systems and methods for computer memory management are described herein. A system includes a memory controller to: monitor utilization of a memory device, the memory device used with a memory compression technique; determine that the utilization of the memory device violates a threshold; and initiate a system interrupt to provoke a response, responsive to the utilization of the memory device violating the threshold.

Memory pressure notifier

Loading data from a computer memory system is disclosed. A memory system is provided, wherein some or all data stored in the memory system is organized as one or more pointer-linked data structures. One or more iterator registers are provided. A first pointer chain is loaded, having two or more pointers leading to a first element of a selected pointer-linked data structure to a selected iterator register. A second pointer chain is loaded, having two or more pointers leading to a second element of the selected pointer-linked data structure to the selected iterator register. The loading of the second pointer chain reuses portions of the first pointer chain that are common with the second pointer chain. Modifying data stored in a computer memory system is disclosed. A memory system is provided. One or more iterator registers are provided, wherein the iterator registers each include two or more pointer fields for storing two or more pointers that form a pointer chain leading to a data element. A local state associated with a selected iterator register is generated by performing one or more register operations relating to the selected iterator register and involving pointers in the pointer fields of the selected iterator register. A pointer-linked data structure is updated in the memory system according to the local state.

Iterator register for structured memory

Growing community of inventors

Mountain View, CA, United States of America

Amin Firoozshahian