Alibaba Damo (hangzhou) Technology Co., Ltd.

Alibaba (china) Co., Ltd.

Shengcheng Wang

Hongzhong Zheng

Dimin Niu

Yuhao Wang

Shuangchen Li

Yijin Guan

Yen-kuang Chen

Tianchan Guan

Lide Duan

Qichen Zhang

Bowen Huang

The present application discloses a computing system for implementing an artificial neural network model. The artificial neural network model has a structure of multiple layers. The computing system comprises a first processing unit, a second processing unit, and a third processing unit. The first processing unit performs computations of the first layer based on a first part of input data of the first layer to generate a first part of output data. The second processing unit performs computations of the first layer based on a second part of the input data of the first layer so as to generate a second part of the output data. The third processing unit performs computations of the second layer based on the first part and the second part of the output data. The first processing unit, the second processing unit, and the third processing unit have the same structure.

Computing system for implementing artificial neural network models and method for implementing artificial neural network models

A computer-implemented method for allocating memory bandwidth of multiple CPU cores in a server includes: receiving an access request to a last level cache (LLC) shared by the multiple CPU cores in the server, the access request being sent from a core with a private cache holding copies of frequently accessed data from a memory; determining whether the access request is an LLC hit or an LLC miss; and controlling a memory bandwidth controller based on the determination. The memory bandwidth controller performs a memory bandwidth throttling to control a request rate between the private cache and the last level cache. The LLC hit of the access request causes the memory bandwidth throttling initiated by the memory bandwidth controller to be disabled and the LLC miss of the access request causes the memory bandwidth throttling initiated by the memory bandwidth controller to be enabled.

Systems and methods for memory bandwidth allocation

The presented systems enable efficient and effective network communications. The presented systems enable efficient and effective network communications. In one embodiment a memory device includes a memory module, including a plurality of memory chips configured to store information; and an inter-chip network (ICN)/shared smart memory extension (SMX) memory interface controller (ICN/SMX memory interface controller) configured to interface between the memory module and an inter-chip network (ICN), wherein the ICN is configured to communicatively couple the memory device to a parallel processing unit (PPU). In one exemplary implementation, the ICN/SMX memory controller includes a plurality of package buffers, an ICN physical layer interface, a PRC/MAC interface, and a switch. The memory device and be a memory card including memory module (e.g., DDR DIMM, etc.).

Flexible memory extension systems and methods

The maximum capacity of a very fast memory in a system that requires very fast memory access times is increased by adding a memory with remote access times that are slower than required, and then moving infrequently accessed data from the memory with the very fast access times to the memory with the slow access times.

Processing system that increases the capacity of a very fast memory

The total memory space that is logically available to a processor in a general-purpose graphics processing unit (GPGPU) module is increased to accommodate terabyte-sized amounts of data by utilizing the memory space in an external memory module, and by further utilizing a portion of the memory space in a number of other external memory modules.

Growing community of inventors

Shanghai, China

Shengcheng Wang