Advanced Micro Devices Corporation

Mohamed Assem Abd ElMohsen Ibrahim

Shaizeen Dilawarhusen Aga

Johnathan R Alsop

Nuwan S Jayasena

Mahzabeen Islam

Meysam Taassori

A system and method for efficiently accessing sparse data for a workload are described. In various implementations, a computing system includes an integrated circuit and a memory for storing tasks of a workload that includes sparse accesses of data items stored in one or more tables. The integrated circuit receives a user query, and generates a result based on multiple data items targeted by the user query. To reduce the latency of processing the workload even with sparse lookup operations performed on the one or more tables, a prefetch engine of the integrated circuit stores a subset of data items in prefetch data storage. The prefetch engine also determines which data items to store in the prefetch data storage based on one or more of a frequency of reuse, a distance or latency of access of a corresponding table of the one more tables, or other.

Method for embedding rows prefetching in recommendation models

Systems and techniques for data-driven precision memory access of cache block data are described. Computing system components are informed as to instances where access operations involve deducing a necessary precision of the data format and expressing the requested data in a lower-precision data format with minimal to no accuracy loss. In one example, executable code for a computational task includes hints that identify when memory requests involve accessing data in a numeric data format based on a deduced precision of the stored data during memory access. The described techniques thus overcome conventional drawbacks facing systems that transmit and compute data in a higher-precision data format than required by the stored values.

Data-driven precision for memory access

In accordance with the described techniques for bank-level parallelism for processing in memory, a plurality of commands are received for execution by a processing in memory component embedded in a memory. The memory includes a first bank and a second bank. The plurality of commands include a first stream of commands which cause the processing in memory component to perform operations that access the first bank and a second stream of commands which cause the processing in memory component to perform operations that access the second bank. A next row of the first bank that is to be accessed by the processing in memory component is identified. Further, a precharge command is scheduled to close a first row of the first bank and an activate command is scheduled to open the next row of the first bank in parallel with execution of the second stream of commands.

Bank-level parallelism for processing in memory

In accordance with described techniques for filtered responses to memory operation messages, a computing system or computing device includes a memory system that receives messages. A filter component in the memory system receives the responses to the memory operation messages, and filters one or more of the responses based on a filterable condition. A tracking logic component tracks the one or more responses as filtered responses for communication completion.

Filtered responses of memory operation messages

A virtual padding unit provides a virtual padded data structure (e.g., virtually padded matrix) that provides output values for a padded data structure without storing all of the padding elements in memory. When the virtual padding unit receives a virtual memory address of a location in the virtual padded data structure, the virtual padding unit checks whether the location is a non-padded location in the virtual padded data structure or a padded location in the virtual padded data structure. If the location is a padded location in the virtual padded data structure, the virtual padding unit outputs a padding value rather than a value stored in the virtual padded data structure. If the location is a non-padded location in the virtual padded data structure, a value stored at the location is output.

Virtually padding data structures

An approach allows concurrent execution of near-memory processing commands, referred to herein as 'PIM commands,' and host memory commands. A memory controller determines and issues a plurality of register-only PIM commands that do not reference memory with host memory commands to allow concurrent execution of the register-only PIM commands and the host memory commands. The approach allows concurrent execution of register-only PIM commands and host memory commands without interference, even when the register-only PIM commands and the host memory commands are interleaved, and even for the same memory module, which improves resource utilization and performance. Further improvement of resource utilization and performance is achieved by extending a register-only phase by reordering register-only PIM commands before non-register-only PIM commands, subject to dependency constraints, and using shadow row buffers to provide local working copies of data from memory to near-memory compute elements.

Growing community of inventors

Santa Clara, CA, United States of America

Mohamed Assem Abd ElMohsen Ibrahim