公开(公告)号：US20230289190A1

公开(公告)日：2023-09-14

申请号：US17691288

申请日：2022-03-10

Applicant: NVIDIA Corporation

Inventor： Apoorv PARLE ,  Ronny KRASHINSKY ,  John EDMONDSON ,  Jack CHOQUETTE ,  Shirish GADRE ,  Steve HEINRICH ,  Manan PATEL ,  Prakash Bangalore PRABHAKAR, JR. ,  Ravi MANYAM ,  Wish GANDHI ,  Lacky SHAH ,  Alexander L. Minkin

IPC: G06F9/38 ,  G06F9/52 ,  G06F13/40 ,  G06F13/16 ,  H04L49/101 ,  G06T1/20 ,  G06T1/60

CPC classification number: G06F9/3887 ,  G06F9/522 ,  G06F13/4022 ,  G06F13/1689 ,  H04L49/101 ,  G06T1/20 ,  G06T1/60

Abstract: This specification describes a programmatic multicast technique enabling one thread (for example, in a cooperative group array (CGA) on a GPU) to request data on behalf of one or more other threads (for example, executing on respective processor cores of the GPU). The multicast is supported by tracking circuitry that interfaces between multicast requests received from processor cores and the available memory. The multicast is designed to reduce cache (for example, layer 2 cache) bandwidth utilization enabling strong scaling and smaller tile sizes.

公开(公告)号：US20230289215A1

公开(公告)日：2023-09-14

申请号：US17691621

申请日：2022-03-10

Applicant: NVIDIA Corporation

Inventor： Greg PALMER ,  Gentaro HIROTA ,  Ronny KRASHINSKY ,  Ze LONG ,  Brian PHARRIS ,  Rajballav DASH ,  Jeff TUCKEY ,  Jerome F. DULUK, JR. ,  Lacky SHAH ,  Luke DURANT ,  Jack CHOQUETTE ,  Eric WERNESS ,  Naman GOVIL ,  Manan PATEL ,  Shayani DEB ,  Sandeep NAVADA ,  John EDMONDSON ,  Prakash BANGALORE PRABHAKAR ,  Wish GANDHI ,  Ravi MANYAM ,  Apoorv PARLE ,  Olivier GIROUX ,  Shirish GADRE ,  Steve HEINRICH

IPC: G06F9/48 ,  G06F9/38 ,  G06F9/30 ,  G06F9/54

CPC classification number: G06F9/4881 ,  G06F9/3851 ,  G06F9/3009 ,  G06F9/544

Abstract: A new level(s) of hierarchy—Cooperate Group Arrays (CGAs)—and an associated new hardware-based work distribution/execution model is described. A CGA is a grid of thread blocks (also referred to as cooperative thread arrays (CTAs)). CGAs provide co-scheduling, e.g., control over where CTAs are placed/executed in a processor (such as a GPU), relative to the memory required by an application and relative to each other. Hardware support for such CGAs guarantees concurrency and enables applications to see more data locality, reduced latency, and better synchronization between all the threads in tightly cooperating collections of CTAs programmably distributed across different (e.g., hierarchical) hardware domains or partitions.

公开(公告)号：US20170123978A1

公开(公告)日：2017-05-04

申请号：US14925922

申请日：2015-10-28

Applicant: NVIDIA CORPORATION

Inventor： Praveen KRISHNAMURTHY ,  Peter B. HOLMQUIST ,  Wishwesh GANDHI ,  Timothy PURCELL ,  Karan MEHRA ,  Lacky SHAH

IPC: G06F12/08 ,  G06F3/06

CPC classification number: G06F12/0802 ,  G06F3/0608 ,  G06F3/064 ,  G06F3/0673 ,  G06F12/0842 ,  G06F12/0844 ,  G06F12/0848 ,  G06F12/0851 ,  G06F12/0853 ,  G06F12/0895 ,  G06F2212/1016 ,  G06F2212/401 ,  G06F2212/608

Abstract: In one embodiment of the present invention a cache unit organizes data stored in an attached memory to optimize accesses to compressed data. In operation, the cache unit introduces a layer of indirection between a physical address associated with a memory access request and groups of blocks in the attached memory. The layer of indirection—virtual tiles—enables the cache unit to selectively store compressed data that would conventionally be stored in separate physical tiles included in a group of blocks in a single physical tile. Because the cache unit stores compressed data associated with multiple physical tiles in a single physical tile and, more specifically, in adjacent locations within the single physical tile, the cache unit coalesces the compressed data into contiguous blocks. Subsequently, upon performing a read operation, the cache unit may retrieve the compressed data conventionally associated with separate physical tiles in a single read operation.

公开(公告)号：US20240289132A1

公开(公告)日：2024-08-29

申请号：US18660763

申请日：2024-05-10

Applicant: NVIDIA Corporation

Inventor： Apoorv PARLE ,  Ronny KRASHINSKY ,  John EDMONDSON ,  Jack CHOQUETTE ,  Shirish GADRE ,  Steve HEINRICH ,  Manan PATEL ,  Prakash Bangalore PRABHAKAR, JR. ,  Ravi MANYAM ,  Wish GANDHI ,  Lacky SHAH ,  Alexander L. Minkin

IPC: G06F9/38 ,  G06F9/52 ,  G06F13/16 ,  G06F13/40 ,  G06T1/20 ,  G06T1/60 ,  H04L49/101

CPC classification number: G06F9/3887 ,  G06F9/522 ,  G06F13/1689 ,  G06F13/4022 ,  G06T1/20 ,  G06T1/60 ,  H04L49/101

Abstract: This specification describes a programmatic multicast technique enabling one thread (for example, in a cooperative group array (CGA) on a GPU) to request data on behalf of one or more other threads (for example, executing on respective processor cores of the GPU). The multicast is supported by tracking circuitry that interfaces between multicast requests received from processor cores and the available memory. The multicast is designed to reduce cache (for example, layer 2 cache) bandwidth utilization enabling strong scaling and smaller tile sizes.

公开(公告)号：US20230289189A1

公开(公告)日：2023-09-14

申请号：US17691690

申请日：2022-03-10

Applicant: NVIDIA Corporation

Inventor： Prakash BANGALORE PRABHAKAR ,  Gentaro HIROTA ,  Ronny KRASHINSKY ,  Ze LONG ,  Brian PHARRIS ,  Rajballav DASH ,  Jeff TUCKEY ,  Jerome F. DULUK, JR. ,  Lacky SHAH ,  Luke DURANT ,  Jack CHOQUETTE ,  Eric WERNESS ,  Naman GOVIL ,  Manan PATEL ,  Shayani DEB ,  Sandeep NAVADA ,  John EDMONDSON ,  Greg PALMER ,  Wish GANDHI ,  Ravi MANYAM ,  Apoorv PARLE ,  Olivier GIROUX ,  Shirish GADRE ,  Steve HEINRICH

IPC: G06F3/06

CPC classification number: G06F3/064 ,  G06F3/0604 ,  G06F3/0679

Abstract: Distributed shared memory (DSMEM) comprises blocks of memory that are distributed or scattered across a processor (such as a GPU). Threads executing on a processing core local to one memory block are able to access a memory block local to a different processing core. In one embodiment, shared access to these DSMEM allocations distributed across a collection of processing cores is implemented by communications between the processing cores. Such distributed shared memory provides very low latency memory access for processing cores located in proximity to the memory blocks, and also provides a way for more distant processing cores to also access the memory blocks in a manner and using interconnects that do not interfere with the processing cores' access to main or global memory such as hacked by an L2 cache. Such distributed shared memory supports cooperative parallelism and strong scaling across multiple processing cores by permitting data sharing and communications previously possible only within the same processing core.

公开(公告)号：US20200043123A1

公开(公告)日：2020-02-06

申请号：US16053341

申请日：2018-08-02

Applicant: NVIDIA Corporation

Inventor： Rajballav DASH ,  Gregory PALMER ,  Gentaro HIROTA ,  Lacky SHAH ,  Jack CHOQUETTE ,  Emmett KILGARIFF ,  Sriharsha NIVERTY ,  Milton LEI ,  Shirish GADRE ,  Omkar PARANJAPE ,  Lei YANG ,  Rouslan DIMITROV

IPC: G06T1/20 ,  G06F9/38

Abstract: A parallel processing unit (e.g., a GPU), in some examples, includes a hardware scheduler and hardware arbiter that launch graphics and compute work for simultaneous execution on a SIMD/SIMT processing unit. Each processing unit (e.g., a streaming multiprocessor) of the parallel processing unit operates in a graphics-greedy mode or a compute-greedy mode at respective times. The hardware arbiter, in response to a result of a comparison of at least one monitored performance or utilization metric to a user-configured threshold, can selectively cause the processing unit to run one or more compute work items from a compute queue when the processing unit is operating in the graphics-greedy mode, and cause the processing unit to run one or more graphics work items from a graphics queue when the processing unit is operating in the compute-greedy mode. Associated methods and systems are also described.

公开(公告)号：US20170123977A1

公开(公告)日：2017-05-04

申请号：US14925920

申请日：2015-10-28

Applicant: NVIDIA CORPORATION

Inventor： Praveen KRISHNAMURTHY ,  Peter B. HOLMQUIST ,  Wishwesh GANDHI ,  Timothy PURCELL ,  Karan MEHRA ,  Lacky SHAH

IPC: G06F12/08 ,  G06F3/06

CPC classification number: G06F12/0802 ,  G06F3/0608 ,  G06F3/064 ,  G06F3/0673 ,  G06F2212/608

Abstract: In one embodiment of the present invention a cache unit organizes data stored in an attached memory to optimize accesses to compressed data. In operation, the cache unit introduces a layer of indirection between a physical address associated with a memory access request and groups of blocks in the attached memory. The layer of indirection—virtual tiles—enables the cache unit to selectively store compressed data that would conventionally be stored in separate physical tiles included in a group of blocks in a single physical tile. Because the cache unit stores compressed data associated with multiple physical tiles in a single physical tile and, more specifically, in adjacent locations within the single physical tile, the cache unit coalesces the compressed data into contiguous blocks. Subsequently, upon performing a read operation, the cache unit may retrieve the compressed data conventionally associated with separate physical tiles in a single read operation.