The present Application for Patent is related to the following co-assigned, co-pending U.S. patent applications:
Ser. No. 11/435,454, entitled “GRAPHICS SYSTEM WITH DYNAMIC REPOSITION OF DEPTH ENGINE,” filed on May 16, 2006;
Ser. No. 11/412,678, entitled “GRAPHICS SYSTEM WITH CONFIGURABLE CACHES,” filed on Apr. 26, 2006;
Ser. No. 11/445,100, entitled “MULTI-THREADED PROCESSOR WITH DEFERRED THREAD OUTPUT CONTROL,” filed on May 31, 2006;
Ser. No. 11/441,696, entitled “GRAPHICS PROCESSOR WITH ARITHMETIC AND ELEMENTARY FUNCTION UNITS,” filed on May 25, 2006; and
Ser. No. 11/453,436, entitled “CONVOLUTION FILTERING IN A GRAPHICS PROCESSOR,” filed on Jun. 14, 2006, which are all expressly incorporated by reference herein.
1. Field
Various embodiments of the invention pertain to memory management in processor architectures, and particularly to a multi-threaded processor that may internally reorder output instruction threads.
2. Background
Multi-threaded processors are designed to improve processing performance by efficiently executing multiple data streams (i.e., threads) at once within a single processor. Multiple registers are typically used to maintain the state of multiple threads of execution at one time. Multi-threaded architectures often provide more efficient utilization of various processor resources, and particularly the execution logic or arithmetic logic unit (ALU) within the processor. By feeding multiple threads to the ALU, clock cycles that would otherwise have been idle due to a stall or other delays in the processing of a particular thread may be utilized to service a different thread.
One application of multi-threaded processors is for graphics processors or circuits, which may be used to render 2-dimensional (2-D) and 3-dimensional (3-D) images for various applications such as video games, graphics, computer-aided design (CAD), simulation and visualization tools, imaging, etc. These images are typically represented by pixels or vectors having various attributes, such as position coordinates, color values, and texture attributes. A graphics processor may employ a shader core to perform certain graphics operations such as shading. Shading is a highly complex graphics operation involving lighting, shadowing, etc. The shader core may be configured to compute transcendental elementary functions that may be approximated with polynomial expressions, which may then be evaluated with relatively simple instructions executed by an ALU.
As part of a multi-threaded processor's operation, thread registers are temporarily stored in an internal memory file for read and/or write operations by the ALU. Such thread registers may include thread input and/or output data, for example. Typically, the internal memory file is divided into a limited number of pre-defined storage spaces. The pre-defined memory spaces are typically the same size and one or more contiguously addressed memory spaces may be assigned or allocated to one or more registers of a particular thread. For instance, memory spaces may be allocated based on a relative addressing scheme where the storage addresses are offsets from a particular beginning address. As content from registers associated with a thread is outputted from the multi-threaded processor, the allocated memory spaces for the thread registers are de-allocated, reused, and/or reallocated to store registers for new threads.
This memory allocation scheme of dividing memory into small size storage spaces is not efficient in terms of area per bit, and is wasteful of the much-needed memory space in a multi-threaded processor core. For instance, if five contiguously addressed memory spaces become available, four of them may be allocated to registers of a new thread. This leaves one unused memory space that may not be used if the subsequent threads need more than one contiguously addressed register. In another example, four contiguously addressed storage spaces for registers may be available but a new thread requires six contiguously addressed storage spaces for registers. The new thread registers cannot be allocated until a large enough area of contiguously addressed memory spaces become available.
Additionally, some thread registers may use only part of an allocated memory space for storage, leaving the remaining memory space unused. That is, when memory spaces are pre-defined, they have a fixed size. In some cases, thread data stored in a register may take-up just a fraction of the storage capacity of the allocated memory space, thereby wasting the unused space.
Thus, a way is needed to more efficiently use and allocate the much needed memory space in an internal register file of multi-threaded processor cores, such as a shader processor.
One feature provides multi-threaded processor having a thread scheduler configured to receive a thread, allocate one or more virtual registers mapped to one or more internal addresses in a unified memory space, and store content of thread registers associated with the thread in the one or more mapped internal addresses in the unified memory space. The thread scheduler determines the size of the received thread registers and dynamically maps the one or more internal addresses in the unified memory space based on the size of the received thread registers. The thread scheduler also de-allocates the one or more virtual registers once the processing unit has processed the thread. The thread scheduler maintains a mapping table of allocated virtual registers mapped to internal addresses in the unified memory space. The mapped internal addresses in the unified memory space may be contiguous or non-contiguous while the one or more virtual registers have contiguous addresses.
A unified register file is coupled to the thread scheduler. The unified register file includes the unified memory space that stores the thread registers. The thread includes pixel data for a plurality of pixels. The unified register file is divided into a plurality of memory banks where the pixel data is stored across two or more of the plurality of memory banks.
A processing unit is coupled to the unified register file and configured to retrieve content of thread registers from the internal addresses in the unified memory space based on the virtual register mapping. The processing unit is configured to (a) process data in the thread to obtain a result, and (b) store the result to one or more other virtual registers mapped to one or more other internal addresses in the unified memory space. The unified register file includes a plurality of simultaneous read and write ports that permit stored content for thread registers to be read from the memory banks while content for new thread registers is stored to the same memory banks. This permits the processing unit to retrieve pixel data for two or more pixels stored across two or more memory banks in a single clock cycle.
A method is also provided for (a) receiving a thread at a multi-threaded processor, the thread including associated thread registers, (b) mapping one or more virtual registers to one or more internal addresses in a unified memory space of the multi-threaded processor, (c) allocating the one or more virtual registers to the received thread, and/or (d) storing content of the thread registers in the one or more internal addresses associated with the allocated virtual registers. The one or more internal addresses may be allocated to correspond to the size of the received thread registers.
In the following description, specific details are given to provide a thorough understanding of the embodiments. However, it will be understood by one of ordinary skill in the art that the embodiments may be practiced without these specific details. For example, some circuits may be omitted from block diagrams in order not to obscure the embodiments in unnecessary detail.
Also, it is noted that the embodiments may be described as a process that is depicted as a flowchart, a flow diagram, a structure diagram, or a block diagram. Although a flowchart may describe the operations as a sequential process, many of the operations can be performed in parallel or concurrently. In addition, the order of the operations may be re-arranged. Various parts of figures may be combined. A process is terminated when its operations are completed. A process may correspond to a method, a function, a procedure, a subroutine, a subprogram, etc. When a process corresponds to a function, its termination may correspond to a return of the function to the calling function or the main function.
Moreover, a storage medium may represent one or more devices for storing data, including read-only memory (ROM), random access memory (RAM), magnetic disk storage mediums, optical storage mediums, flash memory devices, and/or other machine readable mediums for storing information. The term “machine readable medium” includes, but is not limited to portable or fixed storage devices, optical storage devices, wireless channels, and various other mediums capable of storing, containing, or carrying instruction(s) and/or data.
Furthermore, embodiments may be implemented by hardware, software, firmware, middleware, microcode, or a combination thereof. When implemented in software, firmware, middleware, or microcode, the program code or code segments to perform the necessary tasks may be stored in a machine-readable medium such as a storage medium or other storage means. A processor may perform the necessary tasks. A code segment may represent a procedure, a function, a subprogram, a program, a routine, a subroutine, a module, a software package, a class, or a combination of instructions, data structures, or program statements. A code segment may be coupled to another code segment or a hardware circuit by passing and/or receiving information, data, arguments, parameters, or memory contents. Information, arguments, parameters, data, and the like, may be passed, forwarded, or transmitted via a suitable means including memory sharing, message passing, token passing, and network transmission, among others.
One novel feature provides a multi-threaded processor having an internal unified memory space that is shared by a plurality of threads and is dynamically assigned to thread registers as needed. Instead of having a memory space with pre-defined memory spaces for thread registers, the memory spaces are grouped into a single larger shared memory space for use by multiple threads, the area efficiency and utilization in the processor core is improved.
Another aspect provides a mapping table that maps available space in the unified memory space so that thread registers, including input and/or output registers, can be stored in available memory addresses, either contiguous or non-contiguous. This improves utilization of memory space by using previously unused memory segments and allowing dynamic sizing of the allocated memory spaces for each thread. Dynamic sizing allows a multi-threaded processor to allocate memory space depending on the type and size of data in a thread register. This feature facilitates storing different types of data together in the unified memory space.
Yet another feature provides an efficient method for storing graphics data in the unified memory space to improve fetch and store operations in the memory space. In particular, pixel data for four pixels in a thread are stored across four memory devices having independent input/output ports that permit the four pixels to be read in a single clock cycle by an ALU for processing.
A plurality of threads 104 from one or more applications or processes are received at an input interface (e.g., multiplexer 106) that multiplexes the threads 104 into a multiplexed thread 105. Input threads 104 may include graphic data, such as pixels, and indicate a specific task to be performed on one or more pixels. For example, threads 104 may be graphic data having a set of pixel attributes, position coordinates (x, y, z, w), pixel colors (red, green, blue, alpha), and texture attributes (u, v). Each application or process may have more than one thread. In addition to graphics data, input threads 104 may have associated virtual registers, instructions, and attributes, which the multi-threaded processor 102 uses to process the threads 104. Thread scheduler 108 may also include context registers for maintaining process-specific instructions, data, etc.
Thread scheduler 108 receives the thread stream 105 and performs various functions to schedule and manage execution of threads 104. For example, thread scheduler 108 may schedule processing of threads 104, determine whether resources needed by a particular thread are available, and move the thread to a unified register file 118 via a load controller 112. Thread scheduler 108 interfaces with load controller 112 in order to synchronize the resources for received threads 104. Thread scheduler 108 may also monitor the order in which threads 104 are received from a particular application and cause the results for those threads to be outputted in the same order or sequence as they were received.
Thread scheduler 108 selects active threads for execution, checks for read/write port conflicts among the selected threads and, if there are no conflicts, sends instruction(s) for one thread into an ALU 110 and sends instruction(s) for another thread to load controller 112. At the request of thread scheduler 108, load controller 112 may also be configured to obtain data associated with a thread (from texture engine 126) and instructions associated with a thread from an external source (e.g., a global data cache 124 and/or an external memory device, etc.). In addition to issuing fetch requests for missing instructions, load controller 112 loads thread data into unified register file 118 and associated instructions into instruction cache 114. Thread scheduler 108 also removes threads that have been processed by ALU 110.
ALU 110 may be a single quad ALU or four scalar ALUs. In one implementation, ALU 110 may perform pixel-parallel processing on one component of an attribute for up to four pixels. Alternatively, ALU 110 may perform component-parallel processing on up to four components of an attribute for a single pixel. ALU 110 fetches data from register file 118 and receives constants from constant RAM 116. Ideally, ALU 110 processes data at every clock cycle so that it is not idle, thereby increasing processing efficiency. ALU 110 may include multiple read and write ports on an interface to register file 118 so that it is able to write out thread results while new thread data is fetched/read on each clock cycle.
Multi-threaded processor 102 may be a programmable processor configured to efficiently process particular types of data streams. For example, multi-threaded processor 102 may include constant data for efficiently processing multi-media data streams (e.g., video, audio, etc.). For this purpose, constant RAM 116 may be included in multi-threaded processor 102 to enable load controller 112, under the direction of thread scheduler 108, to load application-specific constant data to efficiently process particular types of instructions. For instance, an instruction cache 114 stores instructions for the threads to provide instructions to thread scheduler 108. Under the control of thread scheduler 108, load controller 112 loads instruction cache 114 with instructions from global data cache 124 and loads constant RAM 116 and unified register file 118 with data from global data cache 124 and/or texture engine 126. The instructions indicate specific operations to be performed for each thread. Each operation may be an arithmetic operation, an elementary function, a memory access operation, etc.
Constant RAM 116 stores constant values used by ALU 110. Unified register file 118 may store temporary results as well as final results from ALU 110 for threads. An output interface (e.g., demultiplexer 120) receives the final results for the executed threads from unified register file 118 and provides these results to the corresponding applications.
One feature provides a register map table for each received or processed thread that maps contiguous virtual register addresses into a unified physical memory space in unified register file 118. For instance, thread scheduler 108 may map a unified memory space in unified register file 118 into contiguous virtual register addresses that can be allocated to threads. Rather than utilizing a memory space divided into pre-defined memory segments to store thread registers, unified register file 118 may be treated as a unified memory space that is shared among all threads. By mapping virtual registers into the unified memory space, the memory space is used more efficiently, with less wasted storage space, and allows allocating virtual registers of different sizes as needed by each type of thread.
In various implementations, the mapped registers in unified memory space 206 may be of different sizes. Virtual addressing allows multiple registers of different sizes to be efficiently stored in unified memory space 206 in unified register file 202. Once execution of a thread has been completed and its results have been outputted, the memory space allocated to the thread registers may be de-allocated, resized, and/or reassigned to store other registers for other threads. This is done by the thread scheduler keeping track of what memory spaces are available and which memory spaces have been allocated to thread registers.
In one implementation, a thread can be written through eight write ports 312 into the memory banks 304, 306, 308, and 310 and simultaneously, in the same clock cycle, another thread can be read from memory banks 304, 306, 308, and 310 through eight read ports 314.
In another implementation, each memory bank 304, 306, 308 and 310 is logically split into two segments of one write port 316 and one read port 320 each.
Another feature provides an efficient method for storing graphic data in virtual registers in the unified memory space to improve fetch and store operations from the memory space.
In many cases, it is desirable to operate on groups of four pixels in two-by-two (2×2) grids of an image to be rendered. Processing of four pixels in a two-by-two (2×2) grid may be performed in several manners.
In one implementation, pixel data for different threads 510, 512, 514, and 516 is stored across the four memory banks 502, 504, 506, and 508. Each memory bank includes mapped virtual registers for storing position coordinates 518, color attributes 520, and texture attributes 522 and 524 for pixels in a thread. Each pixel P0, P1, P2 and P3 is represent by x, y, z, w coordinates (i.e., pixel 0=P0.X, P0.Y, P0.Z, P0.W; pixel 1=P1.X, P1.Y, P1.Z, P1.W; pixel 2=P2.X, P2.Y, P2.Z, P2.W; and pixel 3=P3.X, P3.Y, P3.Z, P3.W) stored across the four memory banks 502, 504, 506, and 508. For instance, a first register 518 in Bank 0502 stores the position x coordinates for the four pixels P0, P1, P2, and P3 in Thread 0510.
Color attributes (i.e., Red, Green, Blue, Alpha-r, g, b, a) for pixels P0, P1, P2 and P3 are similarly stored (i.e., red=P0.R, P1.R, P2.R, P3.R; green=P0.G, P1.G, P2.G, P3.G; blue=P0.B, P1.B, P2.B, P3.B; and alpha=P0.A, P1.A, P2.A, P3.A) across the four memory banks 502, 504, 506, and 508. For instance, a second register 520 can be used to store the red (R) color value for the four pixels (i.e., P0, P1, P2, and P3).
A third and fourth registers 522 and 524 may be used to store texture attributes, such as (u, v), associated with the particular pixels P0, P1, P2, and P3. For instance, P0.u0, P1.u0, P2.u0, P3.u0 in register 522 in Bank 0 represent part of texture attribute u for pixels P0, P1, P2, and P3, respectively.
By storing pixel data in registers across multiple memory banks, scalar operations may be performed more efficiently by an ALU processor. For example, if a scalar operation P0.X+P0.Y is to be performed on coordinates X and Y of pixel P0, the pixel data for P0.X is fetched from Bank 0502 and, simultaneously, pixel data for P0.Y is fetched from Bank 1504. By storing pixel data for a pixel across several RAM devices such data can be fetched by an ALU processor in a single clock cycle.
In one implementation, each register 518, 520, 522, and 524 can store one hundred twenty-eight (128) bits. Thus, each position coordinate (x, y, z, w) and color attribute (r, g, b, a) may be represented by thirty-two (32) bits while the texture attributes may be represented in one hundred twenty-eight (128) bits.
By storing pixel coordinates and attributes in the manner illustrated in
Unified register file 604 may be divided into four memory banks 606, 608, 610, and 612, each having two input (write) ports and two output (read) ports. Memory banks 606, 608, 610, and 612 may store thread registers containing pixel data (e.g., position coordinates, colors and/or texture attributes) organized as illustrated in
The data storage arrangement illustrated in
To process the data for four pixels in one clock cycle, the four ALUs 624, 626, 628, and 630 processes one pixel each. The pixel data can then be sent to the four ALUs 624, 626, 628, and 630 (quad core) which are coupled to unified register file 604 so that four pixels P0, P1, P2, P3 for a particular thread can be processed simultaneously on the same clock cycle with each ALU processing one of the four pixels.
In one implementation, graphics processor 702 also includes supporting components, such as a texture engine 710 that performs specific graphic operations such as texture mapping, and a cache memory 712 that is a fast memory that can store data and instructions for multi-threaded processor 704 and texture engine 710. Cache memory 712 may be coupled to an external main memory 714 through which it can receive data or instructions for particular threads.
Multi-threaded processor 704 may include an internal memory device in which a unified memory space is utilized for storing threads 706. The unified memory space is mapped as virtual registers that can be reallocated and resized to store new thread registers and/or support different data types or sizes as illustrated in
Graphics processor 702 and/or multi-threaded processor 704 (e.g., shader core) may be implemented in various hardware units, such as application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing device (DSPDs), programmable logic devices (PLDs), field programmable gate array (FPGAs), processors, controllers, micro-controllers, microprocessors, and other electronic units.
Certain portions of graphics processor 702 or multi-threaded processor 704 may be implemented in firmware and/or software. For example, a thread scheduler and/or load control unit (e.g., in multi-threaded processor 704) may be implemented with firmware and/or software code (e.g., procedures, functions, and so on) that perform the functions described herein. The firmware and/or software codes may be stored in a memory (e.g., cache memory 712 or main memory 714) and executed by multi-threaded processor 704.
Accordingly, a multi-threaded processor is provided comprising: (a) means for receiving a thread having associated thread registers, (b) means for mapping one or more virtual registers to one or more internal addresses in a unified memory space, (c) means for allocating one or more virtual registers to the thread registers, and (d) means for storing content of the thread registers in the one or more internal addresses associated with the allocated virtual registers.
One or more of the components, steps, and/or functions illustrated in
Those of skill would further appreciate that the various illustrative logical blocks, modules, circuits, and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both. To clearly illustrate this interchangeability of hardware and software, various illustrative components, blocks, modules, circuits, and steps have been described above generally in terms of their functionality. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the overall system.
It should be noted that the foregoing embodiments are merely examples and are not to be construed as limiting the invention. The description of the embodiments is intended to be illustrative, and not to limit the scope of the claims. As such, the present teachings can be readily applied to other types of apparatuses and many alternatives, modifications, and variations will be apparent to those skilled in the art.
Number | Name | Date | Kind |
---|---|---|---|
3469244 | Perotto | Sep 1969 | A |
4079452 | Larson et al. | Mar 1978 | A |
4361868 | Kaplinsky | Nov 1982 | A |
5517611 | Deering | May 1996 | A |
5590326 | Manabe | Dec 1996 | A |
5598546 | Blomgren | Jan 1997 | A |
5777629 | Baldwin | Jul 1998 | A |
5793385 | Nale | Aug 1998 | A |
5794016 | Kelleher | Aug 1998 | A |
5798770 | Baldwin | Aug 1998 | A |
5831640 | Wang et al. | Nov 1998 | A |
5870579 | Tan | Feb 1999 | A |
5872729 | Deolaliker | Feb 1999 | A |
5913059 | Torii | Jun 1999 | A |
5913925 | Kahle et al. | Jun 1999 | A |
5949920 | Jordan et al. | Sep 1999 | A |
5958041 | Petolino, Jr. et al. | Sep 1999 | A |
5991865 | Longhenry et al. | Nov 1999 | A |
6092175 | Levy et al. | Jul 2000 | A |
6188411 | Lai | Feb 2001 | B1 |
6219769 | Strongin et al. | Apr 2001 | B1 |
6226604 | Ehara et al. | May 2001 | B1 |
6279099 | Van Hook et al. | Aug 2001 | B1 |
6466221 | Satoh et al. | Oct 2002 | B1 |
6480941 | Franke et al. | Nov 2002 | B1 |
RE37944 | Fielder et al. | Dec 2002 | E |
6493741 | Emer et al. | Dec 2002 | B1 |
6515443 | Kelly et al. | Feb 2003 | B2 |
6516443 | Zook | Feb 2003 | B1 |
6549209 | Shinohara et al. | Apr 2003 | B1 |
6570570 | Suzuki et al. | May 2003 | B1 |
6574725 | Kranich et al. | Jun 2003 | B1 |
6577762 | Seeger et al. | Jun 2003 | B1 |
6593932 | Porterfield | Jul 2003 | B2 |
6614847 | Das et al. | Sep 2003 | B1 |
6636214 | Leather et al. | Oct 2003 | B1 |
6654428 | Bose et al. | Nov 2003 | B1 |
6693719 | Gupta et al. | Feb 2004 | B1 |
6697063 | Zhu | Feb 2004 | B1 |
6717583 | Shimomura et al. | Apr 2004 | B2 |
6734861 | Van Dyke et al. | May 2004 | B1 |
6744433 | Bastos et al. | Jun 2004 | B1 |
6792575 | Samaniego et al. | Sep 2004 | B1 |
6807620 | Suzuoki et al. | Oct 2004 | B1 |
6825843 | Allen et al. | Nov 2004 | B2 |
6891533 | Alcorn et al. | May 2005 | B1 |
6891544 | Oka et al. | May 2005 | B2 |
6950927 | Apisdorf et al. | Sep 2005 | B1 |
6952213 | Ebihara | Oct 2005 | B2 |
6952440 | Underbrink | Oct 2005 | B1 |
6958718 | Symes et al. | Oct 2005 | B2 |
6964009 | Samaniego et al. | Nov 2005 | B2 |
6972769 | Nebeker et al. | Dec 2005 | B1 |
6999076 | Morein | Feb 2006 | B2 |
7006881 | Hoffberg et al. | Feb 2006 | B1 |
7015913 | Lindholm et al. | Mar 2006 | B1 |
7015914 | Bastos et al. | Mar 2006 | B1 |
7027062 | Lindholm et al. | Apr 2006 | B2 |
7027540 | Wilson et al. | Apr 2006 | B2 |
7030878 | Xu et al. | Apr 2006 | B2 |
7034828 | Drebin et al. | Apr 2006 | B1 |
7068272 | Voorhies et al. | Jun 2006 | B1 |
7088371 | Lippincott | Aug 2006 | B2 |
7098922 | Bastos et al. | Aug 2006 | B1 |
7130443 | Werner et al. | Oct 2006 | B1 |
7145565 | Everitt et al. | Dec 2006 | B2 |
7146486 | Prokopenko et al. | Dec 2006 | B1 |
7174224 | Hudson et al. | Feb 2007 | B2 |
7196708 | Dorojevets et al. | Mar 2007 | B2 |
7239322 | Lefebvre et al. | Jul 2007 | B2 |
7239735 | Nozaki | Jul 2007 | B2 |
7268785 | Glanville et al. | Sep 2007 | B1 |
7339592 | Lindholm et al. | Mar 2008 | B2 |
7358502 | Appleby et al. | Apr 2008 | B1 |
7372484 | Mouli | May 2008 | B2 |
7379067 | Deering et al. | May 2008 | B2 |
7388588 | D'Amora et al. | Jun 2008 | B2 |
7447873 | Nordquist | Nov 2008 | B1 |
7557832 | Lindenstruth et al. | Jul 2009 | B2 |
7574042 | Tsuruoka et al. | Aug 2009 | B2 |
7583294 | Ray et al. | Sep 2009 | B2 |
7612803 | Meitav et al. | Nov 2009 | B2 |
7619775 | Kitamura et al. | Nov 2009 | B2 |
7633506 | Leather et al. | Dec 2009 | B1 |
7673281 | Yamanaka et al. | Mar 2010 | B2 |
7683962 | Border et al. | Mar 2010 | B2 |
7684079 | Takata et al. | Mar 2010 | B2 |
7733392 | Mouli | Jun 2010 | B2 |
7738699 | Tsuruoka et al. | Jun 2010 | B2 |
7808505 | Deering et al. | Oct 2010 | B2 |
7813822 | Hoffberg | Oct 2010 | B1 |
7826092 | Ejima et al. | Nov 2010 | B2 |
7904187 | Hoffberg et al. | Mar 2011 | B2 |
7920204 | Miyanari | Apr 2011 | B2 |
7966078 | Hoffberg et al. | Jun 2011 | B2 |
7987003 | Hoffberg et al. | Jul 2011 | B2 |
8046313 | Hoffberg et al. | Oct 2011 | B2 |
8054573 | Mathew et al. | Nov 2011 | B2 |
8154818 | Mathew et al. | Apr 2012 | B2 |
8165916 | Hoffberg et al. | Apr 2012 | B2 |
20020091915 | Parady | Jul 2002 | A1 |
20030034975 | Lindholm et al. | Feb 2003 | A1 |
20030080959 | Morein | May 2003 | A1 |
20030105793 | Guttag et al. | Jun 2003 | A1 |
20030167379 | Soltis, Jr. | Sep 2003 | A1 |
20030172234 | Soltis, Jr. | Sep 2003 | A1 |
20040030845 | DeLano et al. | Feb 2004 | A1 |
20040119710 | Piazza et al. | Jun 2004 | A1 |
20040130552 | Duluk et al. | Jul 2004 | A1 |
20040172631 | Howard | Sep 2004 | A1 |
20040187119 | Janik et al. | Sep 2004 | A1 |
20040246260 | Kim et al. | Dec 2004 | A1 |
20050090283 | Rodriquez | Apr 2005 | A1 |
20050184994 | Suzuoki et al. | Aug 2005 | A1 |
20050195198 | Anderson et al. | Sep 2005 | A1 |
20050206647 | Xu et al. | Sep 2005 | A1 |
20060004942 | Hetherington et al. | Jan 2006 | A1 |
20060020831 | Golla et al. | Jan 2006 | A1 |
20060028482 | Donovan et al. | Feb 2006 | A1 |
20060033735 | Seiler et al. | Feb 2006 | A1 |
20060066611 | Fujiwara et al. | Mar 2006 | A1 |
20060136919 | Aingaran et al. | Jun 2006 | A1 |
20070030280 | Paltashev et al. | Feb 2007 | A1 |
20070070075 | Hsu | Mar 2007 | A1 |
20070185953 | Prokopenko et al. | Aug 2007 | A1 |
20070236495 | Gruber et al. | Oct 2007 | A1 |
20070252843 | Yu et al. | Nov 2007 | A1 |
20070257905 | French et al. | Nov 2007 | A1 |
20070268289 | Yu et al. | Nov 2007 | A1 |
20070273698 | Du et al. | Nov 2007 | A1 |
20070283356 | Du et al. | Dec 2007 | A1 |
20070292047 | Jiao et al. | Dec 2007 | A1 |
20080074433 | Jiao et al. | Mar 2008 | A1 |
Number | Date | Country |
---|---|---|
0627682 | Dec 1994 | EP |
0676691 | Oct 1995 | EP |
0917056 | May 1999 | EP |
3185521 | Aug 1991 | JP |
9062852 | Mar 1997 | JP |
9231380 | Sep 1997 | JP |
2000057365 | Feb 2000 | JP |
2001222712 | Aug 2001 | JP |
2001236221 | Aug 2001 | JP |
2001357410 | Dec 2001 | JP |
2002269583 | Sep 2002 | JP |
2002529870 | Sep 2002 | JP |
2006099422 | Apr 2006 | JP |
2137186 | Sep 1999 | RU |
2004109122 | Jun 2007 | RU |
I230869 | Apr 2005 | TW |
0028482 | May 2000 | WO |
WO0215000 | Feb 2002 | WO |
WO2005086090 | Sep 2005 | WO |
Entry |
---|
Waldspurger et al., Register Relocation: Flexible Contexts for Multithreading, International Symposium on Computer Architcture, Proceedings of the 20th Annual International Symposium on Computer Architecture, 1993. |
International Search Report, PCT/US2007/071775—International Searching Authority—European Patent Office—Apr. 21, 2008. |
Written Opinion, PCT/US2007/071775—International Searching Authority—European Patent Office—Apr. 21, 2008. |
Bjorke K: “High quality filtering” Chapter 24 in Book ‘GPU Gems’, [Online] 2004, XP002534488 Retrieved from the Internet: URL:http://http.developer.nvidia.com/GPUGems/gpugerns—ch24.html> [retrieved on Jun. 29, 2009]. |
Blamer K et al.: “A Single Chip Multimedia Video Processor,” Custom Integrated Circuits Conference, pp. 91-94, Proceedings of the IEEE (May 1994). |
Segal, M. et al.: “The OpenGL Graphics System: A Specification,” pp. 1-368, Version 2.0 (Oct. 22, 2004). |
Deering M. et al: “The SAGE graphics architecture” Proceedings of the 29th Annual Conference on Computer Graphics and Interactive Techniques (SIGGRAPH'02), Jul. 23-26, 2002, San Antonio, Texas, USA, 2002, pp. 683-692, XP002534489. |
Hadwiger M. et al: “Hardware-accelerated high-quality filtering on PC hardware” Proceedings of 2001 Conference on Vision, Modelling and Visualization, Nov. 21-23, 2001, Stuttgart, Germany, [Online] 2001, XP002534490 Retrieved from the Internet: URL:http://wwwvis.informatik.uni-stuttgart.de/vmv01/d1/papers/8.pdf> [retrieved on Jun. 29, 2009]. |
Hopf MI et al: “Accelerating 3D convolution using graphics hardware”Visualization '99. Proceedings San Francisco, CA, USA Oct. 24-29, 1999, Piscataway, NJ, USA, IEEE, US, Oct. 29, 1999, pp. 471-564, XP031385575 ISBN: 978-0-7803-5897-3. |
Novasad J: “Advanced high quality filtering” Chapter 27 in Book ‘GPU-Gems 2’, [Online] . 2005, XP002534486 Retrieved from the Internet:. URL:http://http.developer.nvidia.com/GPUGe ms2/gpugems2—chapter27.html> [retrieved on Jun. 29, 2009]. |
Owens J.D et al: “A survey of general-purpose computation on graphics hardware” Computer Graphics Forum, vol. 26, No. 1, Mar. 2007, pp. 80-113, XP002534491. |
Sigg C. et al: “Fast third-order texture filtering” Chapter 20 in Book ‘GPU Gems 2’, [Online] 2005, XP002534487 Retrieved from the Internet: URL:http://http.developer.nvidia.com/GPUGe ms2/gpugems2—chapter20.html> [retrieved on Jun. 29, 2009]. |
Kilgariff et al.; “Chapter 30, The GeForce 6 Series GPU Architecture:” GPU Gems 2 Copyright 2005, pp. 471-491. |
Lindholm et al.; “A User-Programmable Vertex Engine;” Aug. 12-17, 2001; ACM SIGGRAPH; pp. 149-158. |
Wynn, Chris; “nVIDIA OpenGL Vertex Programming on Future-Generation GPUs;” May 8, 2004; NVIDIA Corporation; pp. 1-97. |
Akkary, H. and Driscoll, M. A. 1998. A dynamic multithreading processor. In Proceedings of the 31st Annual ACM/IEEE international Symposium on Microarchitecture (Dallas, Texas, United States). International Symposium on Microarchitecture. IEEE Computer So. 1998, pp. 226-236. |
Kenji Watanabe, Wanming Chu, Yamin Li, “Exploiting Java Instruction/Thread Level Parallelism with Horizontal Multithreading,” Australasian Computer Systems Architecture Conference, p. 122, 6th Australasian Computer Systems Architecture Conference (AustCSA.) IEEE 2001, pp. 122-129. |
Ying Chen, Resit Sendag, David J. Lilja, “Using Incorrect Speculation to Prefetch Data in a Concurrent Multithreaded Processor,” Parallel and Distributed Processing Symposium, International, p. 76b, International Parallel and Distributed Processing Sympos., IEEE 2003, pp. 1-9. |
Translation of Office Action in Japanese application 2009-511215 corresponding to U.S. Appl. No. 11/435,454, citing WO05086090, US20030080959 and JP2001222712 dated Feb. 22, 2011. |
Hiroaki Hirata, and 4 others, “An elementary processor Architecture with Parallel Instruction Issuing from Multiple Threads,” Information Processing Society article magazine, Information Processing Society of Japan, 1993, vol. 34, No. 4, pp. 595-605. |
Sohn, et al., “A 155-mW 50-Mvertices/s Graphics Processor With Fixed-Point Programmable Vertex Shader for Mobile Application,” IEEE Journal of Solid-State Circuits, vol. 41, No. 5, May 2006, pp. 1081-1091. |
Onoue, M., et al., “3D Image Handbook”, 1st ed., Asakura Publishing Co., Ltd. (Kunizou Asakura), Feb. 20, 2006, pp. 152-170. |
Number | Date | Country | |
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20070296729 A1 | Dec 2007 | US |