Hewlett-Packard Company

Google Inc.

Numecent Holdings, Inc.

Endeavors Technology, Inc.

Hewlett-Packard Development Company, L.p.

Endeavors Technologies, Inc.

Manuel Enrique Benitez

Lacky V Shah

Daniel Arai

Wei C Hsu

Sameer Panwar

Anne Holler

William B Buzbee

James S Mattson

Anne M Holler

Monish Shah

Christopher John Sabol

Daniel Ari Ehrenberg

Thomas Wyatt Craig

Slava Pestov

Robert Curtis Wohlgemuth

Tao Gong

Narges Shahidi

Shashwat Silas

A drive placement or placement functionality can enable initial copies of data to be placed on a drive in reclaim unit (HRUs) in a manner which is probabilistically more efficient from a garbage collection (GC) perspective and leverages knowledge of a host or application using the data. The placement functionality enables the advantages of fine-grained placement functionality while simultaneously allowing a storage device or storage drive to maintain NAND or other management responsibility, and not allocate that responsibility to an application or host device using the device.

Storage design for host controlled logically addressed flexible data layout

The subject matter described herein provides systems and techniques to counter a high write amplification in physical memory, to ensure the longevity of the physical memory, and to ensure that the physical memory wears in a more uniform manner. In this regard, aspects of this disclosure include the design of a Flash Translation Layer (FTL), which may manage logical to physical mapping of data within the physical memory. In particular, the FTL may be designed with a mapping algorithm, which uses reinforcement learning (RL) to optimize data mapping within the physical memory. The RL technique may use a Bellman equation with q-learning that may rely on a table being updated with entries that take into account at least one of a state, an action, a reward, or a policy. The RL technique may also make use a deep neural network to predict particular values of the table.

Flash translation layer design using reinforcement learning

An apparatus includes a host device and a data storage device. The host device is configured to store a first translation map for converting a logical sector to a logical erase unit. The data storage device includes a plurality of flash memory devices and a memory controller operationally coupled with the flash memory devices, each of the flash memory devices being arranged into a plurality of erase units, each of the erase units having a plurality of pages for storing data. The memory controller is configured to receive a second translation map from the host device, the second translation map for converting a logical erase unit to a physical erase unit within the flash memory devices, and store the second translation map in a memory module on the data storage device.

Use of a logical-to-logical translation map and a logical-to-physical translation map to access a data storage device

Installation of an application on a test bed machine is monitored to generate a streamed application set of a stream enabled version of the application. Execution of the application on the test bed machine is monitored to generate the streamed application set of the stream enabled version of the application. Stream enabled application pages and a stream enabled application install block to form the streamed application set is generated based on the monitoring of the installation of the application and the monitoring of the execution of the application on the test bed machine. The stream enabled application install block is provided to a client device. A request for a stream enabled application page of the stream enabled application pages is received from the client device. The stream enabled application page is provided to the client device for continued execution of the stream enabled version of the application.

Intelligent network streaming and execution system for conventionally coded applications

A data storage device includes a plurality of flash memory devices. A memory controller is configured to receive a request from a host computing device to write a first logical block of application data to the data storage device, write the first logical block to a data buffer, wherein a size of the data buffer is larger than the logical block and may store multiple logical blocks, write one or more logical blocks of garbage-collected data to the data buffer, and write the logical blocks in the data buffer to the data storage device when the data buffer becomes full. The data buffer written to the data storage device includes at least one logical block of application data and at least one logical block of garbage-collected data. In an alternative implementation, garbage-collected data may be written to the data buffer upon expiration of a timer.

Use of application data and garbage-collected data to improve write efficiency of a data storage device

An intelligent network streaming and execution system for conventionally coded applications provides a system that partitions an application program into page segments by observing the manner in which the application program is conventionally installed. A minimal portion of the application program is installed on a client system and the user launches the application in the same ways that applications on other client file systems are started. An application program server streams the page segments to the client as the application program executes on the client and the client stores the page segments in a cache. Page segments are requested by the client from the application server whenever a page fault occurs from the cache for the application program. The client prefetches page segments from the application server or the application server pushes additional page segments to the client based on the pattern of page segment requests for that particular application. The user subscribes and unsubscribes to application programs, whenever the user accesses an application program a securely encrypted access token is obtained from a license server if the user has a valid subscription to the application program. The application server begins streaming the requested page segments to the client when it receives a valid access token from the client. The client performs server load balancing across a plurality of application servers. If the client observes a non-response or slow response condition from an application server or license server, it switches to another application or license server.

In a system that partitions an application program into page segments, a minimal portion of the application program is installed on a client system. The client prefetches page segments from the application server or the application server pushes additional page segments to the client. The application server begins streaming the requested page segments to the client when it receives a valid access token from the client. The client performs server load balancing across a plurality of application servers. If the client observes a non-response or slow response condition from an application server or license server, it switches to another application or license server.

An client-side performance optimization system for streamed applications provides several approaches for fulfilling client-side application code and data file requests for streamed applications. A streaming file system or file driver is installed on the client system that receives and fulfills application code and data requests from a persistent cache or the streaming application server. The client or the server can initiate the prefetching of application code and data to improve interactive application performance. A client-to-client communication mechanism allows local application customization to travel from one client machine to another without involving server communication. Applications are patched or upgraded via a change in the root directory for that application. The client can be notified of application upgrades by the server which can be marked as mandatory, in which case the client will force the application to be upgraded. The server broadcasts an application program's code and data and any client that is interested in that particular application program stores the broadcasted code and data for later use.

Client-side performance optimization system for streamed applications

The inventive mechanism provides fast profiling and effective trace selection. The inventive mechanism partitions the work between hardware and software. The hardware automatically detects which code is executed very frequently, e.g. which code is hot code. The hardware also maintains the branch history information. When the hardware determines that a section or block of code is hot code, the hardware sends a signal to the software. The software then forms the trace from the hot code, and uses the branch history information in making branch predictions.

Hardware/software system for profiling instructions and selecting a trace using branch history information for branch predictions

The inventive mechanism has a run-time optimization system (RTOS) embedded in hardware. When the code is first moved into Icache, a threshold value is set into a counter associated with the instruction or instruction bundle of the particular cache line of the Icache. Each time the instruction or instruction bundle is executed and retired, the counter is decremented by one. When the counter reaches zero, a trap is generated to inform that the code is hot. A trace selector will form a trace starting from the hot instruction (or instruction bundle) from the Icache line. The Icache maintains branch history information for the instructions in each cache line which is used to determine whether a branch should be predicted as taken or fall through. After the trace is formed, it is optimized and stored into a trace memory portion of the physical memory. The mapping between the original code of the trace and the optimized trace in the trace memory is maintained in a mapping table. The processor consults the mapping table to lead the execution to the optimized code in trace memory. Thus, subsequent execution uses the code in trace memory.

System and method using a hardware embedded run-time optimizer

The inventive mechanism uses a cache table to map branch targets. When a fetch instruction is initiated, the inventive mechanism searches the IP-to-TM cache to determine whether the branch target instruction has been optimized and placed into the trace memory. If there is a match with the P-to-TM cache, then the code in the trace is executed. This cache is examined in parallel with Instruction Translation Lookup Buffer (ITLB). If not a match is found in the IP-to-TM cache, the original binary in the physical address provided by the ITLB will be executed.

Growing community of inventors

Cupertino, CA, United States of America

Manuel Enrique Benitez