Cuda texture memory vs constant memory


Maximize Instruction throughput. memory per block (used for sharing data within a block), global memory per grid, constant memory . Reads have some advantages like address modes and interpolation that can be used at no extra cost. memory. Constant Memory. 5) where that pixel is an interpolation between pixel (0,1) and (0,2). Global memory is the actual video memory (GDDR5): Three times faster than the DDR3 used by the CPU, but. However non-uniform constant buffer loads are dead slow. When buffers are used in D3D12, applications have full control on data placement and arrangement associated with copying resource data around, as long as the memory alignment constant memory shared memory texture memory global memory kernels, blocks, pitch, warp. · 4y. around 500 times slower than shared memory! (DRAM versus SRAM). Constant Cache. Global memory can be read and written to by all the FERMI architecture introduces caching mechanisms for global memory accesses (constant and texture are cached since 1. 0 using explicitly texture memory) 64 Kbytes 48 Kbytes A global memory partition (DRAM) Texture cache – CUDA w/ 8800GTX: 38 sec, 12 times faster than SSE! Global Memory Texture Texture Texture Texture Texture Texture Texture Texture Constant Memory GPU Host CUDA Memory Model Overview • Global memory – Main means of communicating R/W Data between host and device – Contents visible to all threads – Long latency access • We will focus on global memory for now – Constant and texture memory will come later Grid Global Memory Block (0, 0) Shared Memory Thread (0, 0) Registers Thread (1, 0 free over a texture, it takes the same time to access the pixel (0,1) than the pixel (0,1. Constant memory is read-only memory initially stored in global memory, but once used, it is held in a special † CUDA 1. Hardware implementation A Set of SIMD multiprocessors with on-chip shared memory CUDA Programming Guide Fig. • Texture Memory is fast read only memory that is optimized to take advantage of two dimensional access patterns. 2. Finally, surface and texture memory use spe-cialized hardware to quickly access and interpolate data from global memory when Shared Memory. But for sure, I will explain more. Another cached memory type is the texture memory, which is cached based on the 2-D spatial locality. NVIDIA hardware has provided 64KB Constant memory Global Memory Thread Program Global Memory Thread Number Constants Texture Registers Features Fully general load/store to GPU memory: Scatter/Gather Programmer flexibility on how memory is accessed Untyped, not limited to fixed texture types Pointer support Constant memory can be used for some values that are assigned before the kernel is run. Officially not cached (GTX280) Little locality – 3D graphics origin. Chapter 7 Texture Memory When we looked at constant memory, we saw how exploiting special memory spaces under the right circumstances can dramatically  为了提高更进一步的访问速度,Constant Memory,Texture Memory和Global Memory也 而页锁定内存可以通过cuda API 来分配,可分页内存的好处是省去了从CPU 到GPU 的 . These are read-only memory spaces accessible by all threads. We want better ones. CUDA is designed for a specific GPU architecture, namely NVIDIA’s Streaming Following the terminologies of CUDA, there are six types of GPU memory space: register, constant memory, shared memory, texture memory, local memory, and global mem-ory. Each type of memory on the device has its advantages and disadvantages. CUDA C PROGRAMMING GUIDE: 5. Because if you use a typical memory, let’s say, RAM, you have to define how to write the data and read the data from it, and of course you have to Forums The Archive > GPGPU Technology & Programming >. Parallelized seeded region growing using CUDA CUDA threads can access data from different memory spaces on device, such as global, shared, constant, texture memory , and registers. 1. Maximize Memory Throughput NVIDIA (2018, p. x has 16 shared memory banks, and CUDA 2. Texture memory is available for reading to all multiprocessors. x devices. • The global, constant, and texture memory spaces are cached and persistent across kernel launches by the same application. CUDA Memory Model Overview • Global memory – Main means of communicating R/W Data between host and device – Contents visible to all threads – Long latency access • We will focus on global memory for now – Constant and texture memory will come later Grid Global Memory Block (0, 0) Shared Memory Thread (0, 0) Registers Thread (1, 0 GPU Memory to Remember • The CUDA memory model contains multiple memory spaces: –Thread, local, block, shared, global, constant and texture memory spaces –Global, constant and texture memory spaces are persistent across kernels –Global, local and texture memory have the greatest access latency intuVision CUDA implementation employs: Constant memory is for read-only data that will not change over the course of a kernel execution; Textture and surface memory are for specialized read-only data mainly used in graphics routines; Access speed: Global, local, texture, surface << constant << shared, regiser. The last important memory type is the shared memory CUDA Memory Model Overview • Global / Video memory –Main means of communicating data between host and device –Contents visible to all GPU threads –Long latency access (400-800 cycles) –Throughput ~200 GBPS • Texture Memory –Read-only (12 KB) –~800 GBPS –Optimized for 2D spatial locality • Constant Memory –Read-only (64 KB Texture memory also offers different addressing modes, as well as data filtering, for some specific data formats (see Texture and Surface Memory). Data placement optimization, i. CUDA Device Memory Alloca,on. In fact, it may go down to a cost of 3 but using more VGPRs and/or additional instructions in the process. CUDA: Global Memory vs Constant vs Texture Fetch Performance. The global, constant, and texture memory spaces are persistent across kernel launches by the same application. The memory hierarchy of a CUDA device has several parts including the global memory, constant memory, shared memory, texture memory, and local memory. Local Memory 1)Slow 2)Uncached. 그림 3: Constant Memory를 사용하는 CUDA 코드 예제. CUDA. Their properties are elaborated in [15], [16]. from publication:  There is a total of 64K constant memory on a CUDA capable device. It means a great overhead for the constant memory due In CUDA/OpenCL you explicitly state that a variable is . x devices (pre-Fermi), constant memory has the property of being cached in a small 8K L1 cache, so subsequent accesses can be very fast. This paper deals with such aspects and proposes a new implementation model for the CNN discrete time image processor on the CUDA platform using a more recent nVidia’s Kepler architecture. The primary attribute of the constant cache is that it can only service one float to a warp in each cycle. Global Memory Read. Here, I define pixel as the part of an image, memory as the CUDA RAM, and thread as the unit processing of CUDA. This memory is rather slow -- latencies of several hundred cycles, if there are no required data in cache. per grid and texture memory per grid. Exemple et optimisation. x hardware that is For further information on textures, see the CUDA C Programming Guide. R/W per-thread local memory. Memory. Texture memory. 0 on page 40 on page says "A texture can be any region of linear memory or a CUDA array". Chapter 7 Texture Memory When we looked at constant memory, we saw how exploiting special memory spaces under the right circumstances can dramatically accelerate applications. A read-only constant cache that is shared by all the scalar processors cores and speeds up reads from OpenCL constant memory. TEXTURE dimensionality Its dimensionality that specifies whether the texture is addressed as a one dimensional array using one texture coordinate, a two-dimensional array using two texture coordinates, or a three-dimensional array using three texture GPGPU-Sim memory unit •Constant cache: A read-only cache for constant memory •A warp can access one constant cache location in a single memory unit cycle •Texture cache: A read-only cache with FIFO retirement •Shared memory: A 16 KB low latency highly-banked per-core •Threads within a block can cooperate via shared memory performance of CUDA applications to use CUDA effectively. Texture memory is read only. Global variable in CUDA. 2 Additional Texture Capabilities. 448 GPU cores cuda event timer Texture memory is cached on chip and designed for Shared memory Local memory Constant memory Texture memory Global memory. It is available to >all< threads, like global memory. In particular, each shader core has access to a 16KB low latency, highly-banked per-core shared memory; to global texture memory with a per-core texture cache; and to global constant memory with a per-core constant cache. CUDA Device Memory Space Overview •Each thread can: – R/W per-thread registers – R/W per-thread local memory – R/W per-block shared memory – R/W per-grid global memory – Read only per-grid constant memory – Read only per-grid texture memory (Device) Grid Constant Memory Texture Memory Global Memory Block (0, 0) Shared Memory Local It is used for specific tasks such as texture memory which can be accessed using CUDA texture functions. ns_attach_image_10941480121931046. CUDA Memory Types Global memory Slow and uncached, all threads Texture memory (read only) Cache optimized for 2D access, all threads Constant memory (read only) Slow, cached, all threads Shared memory Fast, bank conflicts; limited; threads in block Registers Fast, only for one thread Local memory All threads in a CUDA block can share shared memory, and all CUDA blocks running on a given SM can share the physical memory resource provided by the SM. 5 (available in CCC 1. Constant memory: read-only memory, size 64 kB, it is cached, optimized when warp of threads read same location Texture memory: read-only memory, it is cached, the texture cache is optimized for 2D spatial locality, so threads of the same warp that read texture addresses that are close together will achieve best performance. All large read-only data is stored in a small number of arrays in global memory, and texture handles for image textures. Texture memory (read only). Shared Memory Model example: dot product (S&K constant and texture memory: host/threads read. – 176MFLOPS vs. Constant memory  Download scientific diagram | CUDA hardware model with global memory, constant cache, texture cache, registers, and shared memory [17]. 9 GPU Computing with Nvidia CUDA 1 Analogic Corp. 24 ArchViz project made just for this purpose. 4) Constant memory can be used for some values that are assigned before the kernel is run. Device Memory (Global Memory) Global, constant, and texture Set of 32-bit registers per processor On-chip shared memory where the shared memory space resides A read-only constant cache speed up access to the constant memory space A read-only texture cache speed up access to the texture memory space All threads can also access read-only Constant and Texture memory, optimized for different memory usages Very high memory bandwidth can be achieved using a hierarchy of memory Each thread has private local memory Each thread block has fast access to shared memory All threads have slower access to global memory `CUDA chips also have access to registers, for computational uses. However, newer genera- Global, constant, and texture memory spaces are persistent across kernels called by the same application. Texture Memory (  Constant and texture memories are faster to access than global memory because they have a cache. Read only per-grid constant memory. Global memory is an order of magnitude slower. Cbuffer loads: Nvidia Maxwell (and newer GPUs) have a special constant buffer hardware unit. GPU architectural differences [6] * Shared memory would be better served by padding the array width to 31. TLP Example. I'm using the CUDA Visual profiler, and this is the result: Global Memory. • Questions? CPU. Constant. You do this by writing your own CUDA code in a MEX file and calling the MEX file from MATLAB. Texture memory는 graphics applications를 위해서 만들어졌다. This penal-izes the sorting performance. GTX480 caches it. This is providing that there is some potential for data reuse in the memory pattern the application is using. texture memory space constant memory TABLE I COMPARISON OF TERMS USED BY CUDA AND OPENCL TO DESCRIBE VERY SIMILAR CONCEPTS. Variables tested Already in Texture Memory and Memory-Hierarchy Notes: Many blocks can run on the same SM, if the SM has enough local and shared memory for all blocks. Shared memory와 같은 공간에 존재 Texture Memory : N/A Texture Shared : N/A CBU : N/A Total : N/A Double Bit Device Memory : N/A Register File : N/A L1 Cache : N/A L2 Cache : N/A Texture Memory : N/A Texture Shared : N/A CBU : N/A Total : N/A Aggregate Single Bit CUDA Memory Model Overview • Global / Video memory –Main means of communicating data between host and device –Contents visible to all GPU threads –Long latency access (400-800 cycles) –Throughput ~200 GBPS • Texture Memory –Read-only (12 KB) –~800 GBPS –Optimized for 2D spatial locality • Constant Memory –Read-only (64 KB texture memory or constant memory • GPU implementations must access constant memory efficiently, avoid shared memory bank conflicts, coalesce global memory accesses, and overlap arithmetic with global memory latency • Map is padded out to a multiple of the thread block size: – Eliminates conditional handling at the edges, thus also the GPU memory hierarchy remains critical to many GPU applications. Each thread has a private local memory and each thread block has shared A texture can be any region of linear memory or a CUDA array (described in CUDA Arrays). Shared memory has 32 banks, each 32 bit wide. 03f01 Total Memory: 12,00 GB Shader Model: – CUDA Driver Version: 7. Contents visible to all constant, texture, and shared [33]) and our simulator models accesses to each of these memory spaces. GPGPU via Cuda 5. Fig. 1 Textured Fetch vs. The Tesla architecture supports CUDA applications using a scalable processor array. Here we will see how we can use CUDA to alter data in parallel against a vertex buffer. Texture/Surface Memory is read-accesible by all threads, but unlike Constant Memory, it is optimized for 2D spacial locality, and cache hits pull in surrounding values in both x and y directions. Constant memory is on device memory and is cached in the constant cache. (host memory, device memory로 분류된다) 이런식으로 따로 씀으로써 global, constant, texture memory를 CUDA runtime동안 kernel이 접근 가능하게 해주고, device memory allocation, deallocation랑 host memory와 device memory 간 데이터교류 인터페이스도 Memory global, constant, and Memory texture memories • CUDA uses Shared Memory as shared storage visible to all threads in a thread Multithreaded constant memory (~64KB) read only short-latency (cached) and high bandwith when all threads simultaneously access the same location texture memory (read only) CPU can transfer data to/from all per-grid memories. And there is also texture memory. CUDA capable GPUs are constructed with the “Tesla” architecture. the GPU stores 8 bytes for each 4x4 tile in your texture. 6 ♦User-defined data structures (built in texture memory) 10 Memory Model: Global, Constant, and Texture Memories. Introduction. Each time a warp executes a texture function to read from texture memory, this counts as a single fetch. Texture memory: texture memory is yet another type of read-only memory. Memory: global 5. __constant__, declares device variable in constant memory, accessible from all threads, with lifetime of application. Constant Texture Local GPU Multiprocessor Registers Shared Memory Multiprocessor Registers Shared Memory Multiprocessor Registers Shared Memory Constant and Texture Caches L1 / L2 Cache Memory Architecture CUDA Device Memory Space: Review • Each thread can: – Read only per-grid texture memory Constant Memory Texture Memory Global Memory Local Memory Thread (0, 0 Texture binding modes (linear memory, pitchlinear memory, CUDA Array) Texture coordinate offsets for correct linear interpolation 8bit weight quantization during linear interpolation Can't flush texture cache during kernel execution 3D: xy-interpolation (layered textures) vs. 2 – Memory Hierarchy CUDA devices have access to five different types of memory: global, shared, local, constant, and texture. cu. There is a total of 64K constant memory on a CUDA capable device. CUDA - Memory Units Description Registers: Fastest. Memory For texture memory usage, see NVIDIA document. Texture. If you expect threads to access memory addresses which have some coherence, you might want to consider using texture memory to speed up those memory accesses. Texture Memory (Read Only) Constant memory와 같이 읽기만 가능한 memory 영역이다. Hardware implementation SIMD behaviour through constant Memory和global Memory一样都位于DRAM,并且有一个独立的on-chip cache,比直接从constant Memory读取要快得多。 每个SM上constant Memory cache大小限制为64KB。 constant Memory的获取方式不同于其它的GPU内存,对于constant Memory来说,最佳获取方式是warp中的32个thread获取constant different memory regions, including texture and constant memory. The execution time of the 3 methods is almost the same (less than 1% of difference). 2-2. Texture can do some ltering and stu Global, constant, and texture persistent across kernel launches by same app. It's cached by 8 KB for each multiprocessor. The definition of shared memory in CUDA is replaced in OpenCL by local memory: shared is replaced with local OpenCL makes explicit differentiation between CUDA Memories • Registers o R/W per thread o Fast • Shared Memory o R/W per block o Fast • Constant Memory o R/O per grid o Fast (Cached) • Texture Memory o R/O per grid o Fast (Cached) • Global Memory o R/W per grid o Slow 6 CoNStANt memory AND eveNtS 95 7 textUre memory 115 CUDA by Example addresses the heart of the software development challenge by Constant Memory. L1 Cache/shared memory. Only accessible by a thread. constant and, therefore, the compiler knows that it has to allocate those values contiguously in memory, just like any array Texture memory: 1)Read only 2)Cache optimised. g. This is similar to global memory in that it has high capacity but also high latency, but it is located on-chip, so it’s use decreases the bandwidth use to global memory. Registers – fast, has only thread scope. Dec. A texture fetch is a memory request, which incurs transactions from the texture cache. 4) 如果在 CUDA 中把 device memory 的資料,當作使用 texture 的話,那資料會變成是唯讀的,要透過特殊的函式來讀取,沒有辦法進行修改;不過相對的,和 global memory 或 constant memory 比起來,也有不少優點~(詳細資料請參考《CUDA Programming Guide 1. Designed for the graphics pipeline, it is still claimed to be useful for many practical general purpose algorithms. Device Memory (Global Memory) Global, constant, and texture Set of 32-bit registers per processor On-chip shared memory where the shared memory space resides A read-only constant cache speed up access to the constant memory space A read-only texture cache speed up access to the texture memory space CUDA Device Memory Space Overview • Each thread can: R/W per-thread registers R/W per-thread local memory R/W per-block shared memory R/W per-grid global memory Read only per-grid constant memory Read only per-grid texture memory (Device) Grid Constant Memory Texture Memory Global Memory Block (0, 0) Shared Memory Local Memory Thread (0, 0) NVIDIA CUDA Write GPU thread in C variant Texture Memory Average latency vs. – 256-thread Blocks,. texture memory by grid, read only. Constant memory is used to cache values that are shared by all functional units; Texture memory is optimized for texturing operations provided by the hardware; Key Points. ) because it is limited to each kernel. 20 HW and SW Some advantages of OpenCL over Compute Shaders is that it has stricter precision guarantees, exposes more of the memory details, and that it not strictly tied to gpu's and can be run on cpu's and other accelerators more easily. 30. two TBOs won’t make a total of 8). Use intrinsic functions and atomic functions; User single precision rather than double; Avoid branching; reduce instructions, especially sync operations 64 KB read-only constant cache 12 KB texture cache Texture cache memory throughput (GB/s): 739. Unified virtual memory (CUDA 4. Device Memory Hierarchy Per-thread local memory Thread Global memory Grid 0 Block (1,1) Block (0,0) Block (1,0) Block (0,1) Texture memory Constant memory (64k) Tens of kb per block, on-chip, very fast Size up to 6 Gb, high latency Registers are fast, off-chip local memory has high latency Thread Block Per-block shared memory Random access very Memory Thread (1, 0) Registers Block (1, 0) Shared Memory Local Memory Thread (0, 0) Registers Local Memory Thread (1, 0) Registers Host Courtesy DavidKirk/NVIDIA and Wen-mei Hwu/UIUC Name Latency (cycles) Cached Global DRAM – 100s No Local DRAM – 100s No Constant 1s – 10s – 100s Yes Texture 1s – 10s – 100s Yes Shared 1 -- Register 1 -- There are also two additional read-only memory spaces accessible by all threads: the constant and texture memory spaces. In the above example, the computation time was improved by a factor 4x, by only adding 'hwconst modifier to the kernel function. All device kernel code and data must fit within global memory. 4GFLOPS theoretical peak. Texture Memory – A GPU also has texture units and memory which can be taken advantage of in some circumstances. Unlike global memory, texture memory is cached, and is generally read only. These abstractions are exposed to the programmer through a set of language extensions via the CUDA programming environment. The C++ new operator is supported on compute capability 2. Data Movement 2. Texture 가 non-normalize 일 경우에 메모리 범위를 벗어나는 인덱스 참조는. It is also located in the device memory like the global and local memories, but it is cached, so accesses are faster. Constant memory can be used for data that will not change when the kernel is executing. GPU Caches (Hardware Manage) L1 cache SM마다 존재한다. Helpful when global memory coalescing is the main bottleneck. S rk) 6 CUDA Taxonomy — Read only per-grid texture memory (Device) Grid Constant Memory Texture Memory Global Memory Block (0, 0) Thread­level memory­sharing supported via Shared Memory Register memory is local to thread, and divided amongst all blocks on SM Registers 8KB SM Instruction Fetch/Dispatch Streaming Core #1 Streaming Core #2 Streaming Core #8 Streaming Core #3 Shared Memory 16KB Texture Memory Cache 5­8 KB Constant Memory Cache 8KB • Threads can share memory with the other Threads in the same Block • Threads can synchronize with other Threads in the same Block • Global, Constant, and Texture memory is accessible by all Threads in all Blocks • Each Thread has registers and local memory • Each Block can use at most 8,192 registers, divided equally among all Threads The GPU has several different memory spaces, with each having particular features and uses and different speeds and scopes. Textures can be stored compressed or uncompressed in both video memory and system memory. 2 Programming with streams. 0 From CCC 3. It is however quite fast. 63 “CUDA Memory and Cache Architecture”. device memory with texture cache; Texture cache is optimized for 2D data. Use thread- and block-ids to align memory accesses. Non-numerical algorithms. • As GPU has much higher memory bandwidth, significant performance boost can be obtained! • Use texture memory (read-only, cached) can further enhance performance. Page 6. Shared memory 1)Fast 2)Permits exchange of data between threads in block 3)Usually 16KB per SM or 4)Fastest if all threads read from same shared memory location. Topics. 14, 2012 From my experience, accessing texture memory is as fast as accessing constant memory. Only the global memory allows readings and writings. CUDA 에서 host 와 device는 다른 메모리를 쓴다. Discussion in ' This memory is similar to main memory on a CPU: a big buffer of data. Methodology: I copy data from some source (either linear or texture) to some destination (always linear, since texture memory is read only), doing some arithmetic along the way. For uncompressed textures, the general rule of thumb is that it will take the same amount of space in video memory as it does in uncompressed form in system memory. Parallel breadth-first search (BFS) Texture memory global memory. 0 and above) Shared memory CUDA exposes a fast shared memory region that can be shared among threads. CUDA Memory Hierarchy Image courtesy of NVIDIA CUDA Device Memory Space: Review • Each thread can: – Read only per-grid texture memory Constant Memory Texture Memory Global Memory Local Memory Thread (0, 0 CUDA Memory Types Global memory Slow and uncached, all threads Texture memory (read only) Cache optimized for 2D access, all threads Constant memory (read only) Slow, cached, all threads Shared memory Fast, bank conflicts; limited; threads in block Registers Fast, only for one thread Local memory Answer: In CUDA, texture memory is addressed as z-index on hardware side so when you access some data spatially close, it will access to some cached data which is also close in hardware-side too. 5 Constant  CUDA Shared Memory & Synchronization (K&H Ch5, S&K Ch5). 1 5/19/2010 NVIDIA CUDA™ NVIDIA CUDA C Best Practices Guide Texture Memory Constant memory와 비슷; 2차원 array를 다루는 것에 최적화; Hardware 필터링 제공; 기본적으로 graphic에 활용되므로 cuda에서 많이 사용하지는 않는다. SIMD vs SIMT GPU Memory A CUDA Example: Gaussian Elimination Shared memory L1/L2/L3 cache Constant memory Texture memory CUDA Device Memory • Each thread can: – R/W per-thread registers – R/W per-thread local memory – R/W per-block shared memory – R/W per-grid global memory – Read only per-grid constant memory – Read only per-grid texture memory (Device) Grid Constant Memory Texture Memory Global Memory Block (0, 0) Shared Memory Local Memory 그림 3: Constant Memory를 사용하는 CUDA 코드 예제 5. In certain addressing situations, reading device memory through texture fetching can be an advantageous alternative to reading device memory from global or constant memory. We used to do this before. Data filtering. 下圖展示了memory的結構,他們各自都有不用的空間、生命期和cache。 其中constant和texture是隻讀的。最下面這三個global、constant和texture擁有相同的生命週期。 Registers Memory Read-only constant memory Read-only texture memory Source: NVIDIA CUDA Programming manual. ) aims to make the expression of this parallelism as simple as possible, while simultaneously enabling operation on CUDA-capable GPUs designed for GPU Computing with Nvidia CUDA 1 Analogic Corp. Texture Memory. Optimized for 2D, but small Texture memory is cached on the GPU—faster access than global memory Texture memory is ideal for applications where threads Constant memory is also most effective when all threads access the same value at the same time (i. Constant memory can be used to store immutable data visible to all threads. 1》的 5. Abstract—The concept of shared memory is known to engi- TABLE I. 1) •Start with memory request by smallest numbered These differences are caused by the constant memory and the. Textures provide access to arrays with specialized input and output formats. Like constant memory, texture memory is another variety of read-only memory that can improve performance and reduce memory traffic when reads have certain access patterns. Access to the shared memory is in the TB/s. Have special rules. 9, 2015 Registers; Shared memory; Local memory; Constant memory; Texture memory; Global memory. Global, constant and texture memory spaces can be read or written by the host and persist at kernel launches by the same application. 3 Implementation using constant and texture memory . The device memory is  Nov. GPU On-Chip Memory Systems • GPU arithmetic rates dwarf global memory bandwidth • GPUs include multiple fast on-chip memories to help narrow the gap: –Registers –Constant memory (64KB) –Shared memory (48KB / 16KB) –Read-only data cache / Texture cache (~48KB) •Hardware-assisted 1-D, 2-D, 3-D locality A comparison with CUDA constant memory 7 To compare Constant memory Read-only data cache Availability Size Hardware implementation Access Best feature Worst feature Best scenario From CUDA Compute Capability 1. In GTX480, there is a 16kB or 48kB L1 cache per SM for global memory, depending on the shared memory configuration. 1-2 Class 2: - Fundamentals of the finite difference method - Programming model: mapping the discretized model to the GPU threads - Multilevel memory hierarchy - Shared, global, registers, textures, constant, texture memories - Sizes and latency - Blocks - Finite difference implementations using CUDA: Global Memory Thread Program Global Memory Thread Number Constants Texture Registers Features Fully general load/store to GPU memory: Scatter/Gather Programmer flexibility on how memory is accessed Untyped, not limited to fixed texture types Pointer support Constant Memory and Textures. Data caching . implemented in DDR DRAM modules on the GPU card [1], [5]-[7]. In HD5870, there is a line buffer per SIMD, which can be viewed as a limited cache for global memory as it only provides reuse for the accesses in the same wavefront. This is illustrated by Nvidia's recent launch of the CUDA. ) • Code example: Figure 2. TEXTURE dimensionality Its dimensionality that specifies whether the texture is addressed as a one dimensional array using one texture coordinate, a two-dimensional array using two texture coordinates, or a three-dimensional array using three texture Shane Cook, in CUDA Programming, 2013. x. On compute 1. Specifically, we focus on the memory, we use Constant memory. Global memory. Each thread can: R/W per-thread registers. 0 I have tried 3 different versions of the kernel, placing the tables in different locations: in the global memory, as constants, and in textures. Ch. 1 簡介 在執行 CUDA 程式前,都要把資料先從 Host 的記憶體,複製一份到 device 的記憶體中;一般來說,這樣的部分,都是使用 device 的 global memory 來直接進行存取。. In the implementation with OpenCL, constant memory The CUDA approach using textures showed to be the fastest with a speedup CUDA Memory Model. 14, 2016 Following the terminologies of CUDA, there are six types of GPU memory space: register, constant memory, shared memory, texture memory  Apr. R/W per-block shared memory. CUDA Device Memory Space Overview Each thread can: • R/W per-thread registers • R/W per-thread local memory • R/W per-block shared memory • R/W per-grid global memory • Read only per-grid constant memory • Read only per-grid texture memory (Device) Grid Constant Memory Texture Memory Global Memory Block (0, 0) Shared Memory Local Introduction to CUDA Programming Textures Andreas Moshovos Winter 2009 Some material from: Matthew Bolitho’s slides Memory Hierarchy overview Registers Very fast Shared Memory Very Fast Local Memory 400-600 cycles Global Memory 400-600 cycles Constant Memory 400-600 cycles Texture Memory 400-600 cycles 8K Cache What is Texture Memory A block of read-only memory shared by all multi-processors Constant memory on the GPU is entirely different from regular shared memory. They are described in Texture and Surface Memory. CUDA Best Practices Guide Version 3. jherico. The architecture of  Oct. CUDA VS OPENCL. Vector Increment 3. SIMD vs SIMT GPU Memory A CUDA Example: Gaussian Elimination Shared memory L1/L2/L3 cache Constant memory Texture memory Global Memory Thread Program Global Memory Thread Number Constants Texture Registers Features Fully general load/store to GPU memory: Scatter/Gather Programmer flexibility on how memory is accessed Untyped, not limited to fixed texture types Pointer support 如果在 CUDA 中把 device memory 的資料,當作使用 texture 的話,那資料會變成是唯讀的,要透過特殊的函式來讀取,沒有辦法進行修改;不過相對的,和 global memory 或 constant memory 比起來,也有不少優點~(詳細資料請參考《CUDA Programming Guide 1. 24 Read-only texture cache that is shared by all the processors and speeds up reads from the texture memory space. When a read is being broadcast to the threads, constant memory is much faster than texture memory. Further experimentation shows that adding more buffers (whether texture or constant buffers) won’t use 4 more SPGRs (i. For all threads of a half warp, reading from the constant  Note the constant memory cache is the only cache on compute 1. Local memory is implemented as part of the global memory, therefore has a long access latencies too. This can be used as a user-managed cache, enabling higher bandwidth than is possible using texture lookups. OpenCL vs. Global. 3-1. The global, constant, and texture memory spaces are persistent across kernel  3. – memory  For small kerenels we get much resources(registers, shared memory,constant memory, etc. Each SM has a L1 cache for global memory references. The texture and constant memory are for read-only data and are accessible to all the threads in different TBs. Each processor in multiprocessor has its Texture memory data are cached in texture cache (now incorporated into L1/L2 caches) for fast access – Unlike constant memory, texture memory data are expressed in 1D, 2D or 3D arrays to represent 2D/3D data locality – 1D/2D/3D Data are preloaded to texture cache to improve performance Texture memory data are declared with texture keyword constant memory shared memory texture memory global memory kernels, blocks, pitch, warp. Each GPS has a constant memory for read only with shorter latency and higher throughput. Motherboard Except for constant and texture memory, all other memories are R/W. . Device Memory Accesses CUDA C PROGRAMMING GUIDE: Appendix B. 7 global, constant, and texture memory constant, and texture memory. Main means of communicating R/W Data between host and device. To put it short CPU For x=0 to image size Shared memory. On device memory with constant cache. Incorrectly making use of the available memory in your application can can rob you of the performance you desire. Now Let’s Look at Shared Memory •Common Programming Pattern (CUDA Manual 5. The only real differences are that CUDA supports texture memory (we didn't get into that in our CUDA examples) and OpenCL provides for a global / constant memory cache (Nvidias new Fermi GPU adds a global / constant memory cache). Cache optimized for 2D access, all threads. Constant and texture memory. Caching vs non-caching loads (compiler option) 16KB vs 48KB L1 (CUDA call) - Sometimes using shared memory or the texture / constant cache is the best All threads in a CUDA block can share shared memory, and all CUDA blocks running on a given SM can share the physical memory resource provided by the SM. CUDA®: A General-Purpose Parallel Computing Platform and Programming Model. CPU vs GPU (from [9]) aggregates and equi-joins, e. 5. The above diagram shows the scope of each of the memory segments in the CUDA memory hierarchy. `The final type of memory is texture memory. optimizing the placement of data among these different memories, has a significant impact on the performance of HPC applications running on early generations of GPUs. C LANGUAGE EXTENSIONS CUDA学习笔记九 CUDA Tutorial Access CUDA global device variable from host Constant Memory vs Texture Memory vs Global Memory in CUDA 一篇介绍CUDA Memory的好文档 Access CUDA global device variable from host CUDA的纹理内存讲解,来自翻译和补充官方文档 CUDA programming Guide Texture and Surface Memory CUDA支持供GPU处理图形用的纹理硬件和表面(surface)内存,但是只支持一部分功能。从纹理和表面内存中读取数据可以得到很多好处(以后再说)。 47. With the advent of CUDA, the GPU’s sophisticated texture memory can also be used for general-purpose computing. 84) – Shared memory is accessible by the threads in the same threadblock –16KB vs 48KB L1 (CUDA call) •Texture and constant CUDA Device Memory Space Overview ! Each thread can: − R/W per-thread registers − R/W per-thread local memory − R/W per-block shared memory − R/W per-grid global memory − Read only per-grid constant memory − Read only per-grid texture memory ! The host can R/W global, constant, and texture memories (Device) Grid Texture Cache COMP635,F al207(V. The constant memory is cached. Block (0, 0) Shared Memory. • Local Memory • Global Memory • Constant Memory • Texture Memory oin Device Memory Memory Model • Global Memory • Constant Memory • Texture Memory omanaged by host code opersistent across kernels • Introduction • Motivation • Programming Model • Memory Model • CUDA API •Example • Pro & Contra • Trend Outline CUDA API CUDA, with N threads: shared memory global memory local memory constant memory (read-only) texture memory (read-only) CUDA by example memory Constant memory Texture memory Host Another view of the memory hierarchy of a CUDA device Arrows show the read and write permissions Host can only access global, texture and constant memory Note that the global, constant and texture memory spaces are persistent between kernel calls! Allocating Device Memory (Device) Grid Block (0, 0 Constant storage-- memory area of 64 KB (the same concerns modern GPUs), read only for all multiprocessors. , when the threads in a warp all read the same memory location. 不過實際上,有的時候還有別的選擇的~在《 nVidia CUDA 簡介》中一文就有提到,除了 global different memory regions, including texture and constant memory. The last important memory type is the shared memory Texture Memory: 4915,00 MB Ray-tracing: GPU OpenGL Vendor: NVIDIA Corporation Device: NVIDIA GeForce GTX TITAN X OpenGL Engine Version: 2. 下图展示了memory的结构,他们各自都有不用的空间、生命  May 27, 2010 3. 1: CPU vs. • Need to choose appropriate memory types to use. Setup The computer used to do this comparison is a Pen-tium 4 3. GPU architectural differences [6] The usage of loop tiling is correct, but special types of CUDA memories including texture and constant must be written before kernel starts. Textures are supposed to deal better with common memory access patterns, however, it is unclear whether more modern GPUs still benefit from this. memory footprint, stride accesses Two Blocks accessing constant memory L3: Global •Local Memory •Texture Memory •Constant Memory •Registers ns •Occupancy •Concurrent Kernel Execution •Hiding Register Dependencies •Thread and Block Heuristics •Effects of Shared Memory n •Arithmetic Instructions •Memory Instructions w •Branching and Divergence •Branch Predication •Loop Counters Signed vs. 데이터의 값을 visualize하고 싶은 경우 꼭 texture memory를 사용해야 한다고 한다. It is quite similar to that. In this study, we limit our scope to the three common types: global, shared, and texture memory. Constant memory caching Compute 1. I synchronous vs asynchronous memory Further experimentation shows that adding more buffers (whether texture or constant buffers) won’t use 4 more SPGRs (i. The global memory space is not cached by the device. Constants initialized by host . Constant memory is also most effective when all threads access the same value at the same time (i. Memory Allocation & Initialization 1. – Contents visible to all threads. 5. We also learned how to … - Selection from CUDA by Example: An Introduction to General-Purpose GPU Programming [Book] Texture. Feature. But for now, just keep this in mind. CUDA API Functions I Memory Management: cudaMalloc, cudaFree, cudaMemcpy, etc. Jul. It is allocated by compiler from global memory but logically treated as independent unit. Local. Constant memory is cached by the constant cache and is read only (In cuda, "local memory" is the L1 backed memory for spilling registers which is very different from the constant memory). It supports short-latency, high-bandwidth, read-only access by the device when all threads simultaneously access the same location. 2 346. 5 History of 3D. e. 1 Differences Between Host and Device The primary differences occur in threading and memory access: CUDA has a feature called Texture Memory which sounds like mapping a picture to an object. 예) N=10, float *a[N]; x=-1; a[x] 는 a[0] 으로 대체된다. Constant Memory: This is where constants and kernel arguments are stored. All these different kinds of memory, manually managed by the programmer, are what makes GPU programming so much fun! On the CPU, I pine for the ability (indeed, the requirement!) to manually decide what is in the L1, L2, and L3 cache. The global, constant, and texture memory spaces are persistent across kernel launches by the same application, so the lifetime of these three memory spaces is same as the application. memory footprint, stride accesses Two Blocks accessing constant memory L3: Global CUDA Memory Per-thread private local memory Shared memory visible to whole block (lifetime of block) Global memory also constant and texture spaces. customizable memory types (shared memory, constant memory, texture memory, registers). Layer 1 (L1) cache and shared memory is on-chip memory that is shared within thread blocks (CUDA blocks). If shared, how to ensure the memory ordering • Control flow handling • Instruction Set Architecture • Support: – Programming environment – Compiler, debugger, emulator, etc. Texture memory is optimized for 2D spatial locality. cache. Use device memory (transfer data between host and device) cudaMemcpy(void *dst, const void *src, size_t count, enum cudaMemcpyKind kind). 15 GHz) Memory Clock rate: 1566 Mhz CUDA Memory Types. 4 GB, constant 65 KB, 1 CPU vs. Texture Memory: Cache optimized for 2D spatial access pattern . Constant memory is optimized for broadcast, i. So no writing there. The array consists of a number of streaming multiprocessors (SMs). Although texture memory was originally designed for traditional graphics applications, it can also be used quite effectively in some GPU computing applications. 1 (Device) Grid Constant Memory Texture Memory Global Memory Block (0, 0) Shared Memory Local Memor y Thread (0, 0) Register s Local Memor y Thread (1, 0) Register s Block (1, 0) Shared Memory Memor y Thread (0, 0) Register s Memor y Thread (1, 0) Register s Host CUDA Host-Device Data Transfer (cont. NVIDIA CUDA Therefore, the memory accesses are not coalesced, indicating that the texture memory could be appropriate. In addition, CUDA provides two more specialized types of memory: constant and texture. Execution Model and Memory Hierarchy" October 27, 2011! Programming Assignment 3, Due 11:59PM Nov. 6. Contents visible to all Texture memory read only cache optimized for 2D/3D access pattern Constant memory read only where constants and kernel arguments are stored Shared memory read/write fast Local memory read/write used when it does not fit in to registers part of global memory slow but cached Registers read/write fast • local, Constant, and Texture – off-chip NVIDIA and CUDA 13 GPU Hardware 15 Constant Memory 150 Constant memory caching 150 Texture Memory 200 memory Read-only per-grid constant memory Read-only per-grid texture memory CUDA Programming Guide Fig. NVIDIA CUDA Write GPU thread in C variant Texture Memory Average latency vs. Shared memory is a better fit for LUT usage, though 8K is awfully big. All SMs share a second L2 cache. Device Memory (Global Memory) Global, constant, and texture Set of 32-bit registers per processor On-chip shared memory where the shared memory space resides A read-only constant cache speed up access to the constant memory space A read-only texture cache speed up access to the texture memory space NVIDIA CUDA Write GPU thread in C variant Texture Memory Average latency vs. Part. the array index is not a function of the position). A texture can be any region of linear memory or a CUDA array (described in CUDA Arrays). 22, 2010 8. Multiprocessors. Data are fetched by CUDA Device Memory Space Overview •Each thread can: – R/W per-thread registers – R/W per-thread local memory – R/W per-block shared memory – R/W per-grid global memory – Read only per-grid constant memory – Read only per-grid texture memory (Device) Grid Constant Memory Texture Memory Global Memory Block (0, 0) Shared Memory Local • Dual texture, bilinear filtering • 2 pixels per clock (ppc) • 1999 – Riva TNT2 (NV5), DX6 • Faster TNT • 128b memory interface • 32 MB memory • The chip that would not die ☺ Virtua Fighter (SEGA Corporation) NV1 50K triangles/sec 1M pixel ops/sec 1M transistors 16-bit color Nearest filteringNearest filtering 1995 multi-core vs. memory footprint, stride accesses Two Blocks accessing constant memory L3: Global CUDA Memory Model Overview • Global memory – Main means of communicating R/W Data between host and device – Contents visible to all threads – Long latency access • We will focus on global memory for now – Constant and texture memory will come later Grid Global Memory Block (0, 0) Shared Memory Thread (0, 0) Registers Thread (1, 0 Texture L1 L2 ROP ROP L2 512-bit memory interconnect CUDA Device Query (Runtime API) version (CUDART static linking) Total amount of constant memory: 65536 Texture memory and constant memory can be regarded as fast read-only caches. So, Constant Memory is the feature. When programming compute 1. The global, constant, and texture memory spaces are optimized for different memory usages. ) Texture reads are cached  GPU memory allocation, data transfer, execution, resource creation high-latency memory; Stored in device memory (along with constant and texture memory)  Dec. , in [4,5,6,7], but to date, no solution tailored to theta-joins on GPUs has been proposed. Global memory is a large memory accessible by all threads. Read only per-grid texture memory (Device) Grid. CUDA constant memory per grid, read only. Texture memory has implemented additional hardware functions, such as interpolation. 3GB and also normal memory usage is low so I doubt it is problem with actual memory - either graphic or swap file or something else. 84) in particular global memory, shared memory, constant memory, and texture memory. 4. Memory Model: Global, Constant, and Texture Memories. The closest work to us is the consideration of non-indexed nested loops in [4], which can cover theta- Actual video memory usage is 2. Note that VGPRs are usually more precious than SGPRs. The constant memory can be written into and read by the host. Local and global global memory, which is . Texture and Constant Memories. 4 Texture Memory. The use of constant memory may have a dramatic impact on the performance. Improved memory performance depends not Scattered reads code can read from arbitrary addresses in memory. 26, 2016 cudaMemcpy를 사용하면 안 된다고 한다. A great feature of CUDA is its built-in ability to work with OpenGL directly. This allows a CUDA program easy access to data such as texture, pixel buffers or vertex buffers to perform operations against it quickly. The present example demonstrates how you can further improve the performance of stencil operations using two advanced features of the GPU: shared memory and texture memory. 448 GPU cores cuda event timer Texture memory is cached on chip and designed for Memory Hierarchy: Processors have 32-bit registers Multiprocessors have shared memory, constant cache, and texture cache Constant/texture cache are read-only and have faster access than shared memory. cu CUDA le dened by a constant prex value set by host, read-only by kernels exist for lifetime of entire application current GPUs have a 16KB constant cache very useful to avoid wasting precious registers or shared memory on essential constants (Note: literal constants are kept in the code) Lecture 2 CUDA Parallel Threads and Memory Thread Per-thread Private Local Memory Block • Global Memory • Constant Memory • Texture Memory o in DRAM o cached o per Optimize Memory Access nv'D'A Coalesced vs. 400-600 cycles; 8K Cache. Nvidia CUDA documents tell us that constant buffer load gets serialized for each unique address. CUDA Device Memory Space: Review ! Each thread can: ! R/W per-thread registers ! R/W per-thread local memory ! R/W per-block shared memory ! R/W per-grid global memory ! Read only per-grid constant memory ! Read only per-grid texture memory (Device) Grid Constant Memory Texture Memory Global Memory Block (0, 0) Shared Memory Local - CUDA C Programming Guide. 17, 2018 2048 layers Maximum Layered 2D Texture Size, (num) layers 2D=(16384, 16384), 2048 layers Total amount of constant memory: 65536 bytes  Jun. Linear memory is allocated in a single unified address space, which means that separately allocated entities can reference one another via pointers, for example, in a binary tree or linked list. Version 4. Contents visible to all threads. Our proposal is the first one that explicitly targets theta-joins using a GPU. 1 NVIDIA-10. S rk) 6 CUDA Taxonomy — Read only per-grid texture memory (Device) Grid Constant Memory Texture Memory Global Memory Block (0, 0) • Threads can share memory with the other Threads in the same Block • Threads can synchronize with other Threads in the same Block • Global, Constant, and Texture memory is accessible by all Threads in all Blocks • Each Thread has registers and local memory • Each Block can use at most 8,192 registers, divided equally among all Threads The usage of loop tiling is correct, but special types of CUDA memories including texture and constant must be written before kernel starts. (esp. R/W per-grid global memory. Constant memory is a read-only memory, and it is faster than Global memory. The global memory on the Geforce 8800 is 768MB, has a 64KB CUDA Device Memory Space: Review • Each thread can: – R/W per-thread registers – R/W per-thread local memory – R/W per-block shared memory – R/W per-grid global memory – Read only per-grid constant memory – Read only per-grid texture memory (Device) Grid Constant Memory Texture Memory Global Memory Block (0, 0) Shared Memory Local CUDA Memory Model Grid Constant Memory Texture Memory Global Memory Block (0, 0) Shared Memory Local Memory Thread (0, 0) Registers Local Memory Thread (1, 0) Registers Block (1, 0) Shared Memory Local Memory Thread (0, 0) Registers Local Memory Thread (1, 0) Registers All threads can also access read-only Constant and Texture memory, optimized for different memory usages Very high memory bandwidth can be achieved using a hierarchy of memory Each thread has private local memory Each thread block has fast access to shared memory All threads have slower access to global memory Shared Memory. Thread (0, 0 Block = a group of thread which share “the shared memory space” Warp warp warp warp Memory Space Space ~= CPU Local Memory Within Threads Stack Shared Memory Within Blocks Distributed memory space Global Memory All Centralized storage Constant Memory All Centralized read-only storage (very small) Texture Memory All Centralized read-only storage Texture (1) Texture fetching is much more expensive than any arithmetic instruction When possible, always use compressed texture Better cache performance Less memory footprint Textures remain compressed in L1 cache DXT1 is better than DXT5, performance wise of ‘shared memory’, which is a software-managed data cache; a read-only constant memory cache; and a read-only texture memory cache. Cached global memory (Texture and Constant) CUDA Device Memory ILP vs. 02. Problem occured when I downloaded bought asset pack into empty and clean UE4 2. Local memory is in scope of each thread. 2213 GPU Multiprocessor N Multiprocessor 2 Multiprocessor 1 Global memory Shared memory Control Unit Texture data is much more likely to be larger, accessed repeatedly, and benefit from the improved cache-coherency of non-linear memory layouts than other resource data. What is Texture Memory. Can someone give / refer me to a really simple (Texture memory for dummies) example of how texture is used and improves performance. on-chip cache. Shared Memory in CUDA A special type of memory whose contents are explicitly declared and used in the source code Memory Spaces •Register, local, shared, global, constant (read only), and texture (read only) memory are the memory spaces available. As it is shown, a thread (executed on a processor within a multiprocessor) have a access to 6 di erent types of memory: register, local, shared, global (device), constant and texture memory. TEXTURE dimensionality Its dimensionality that specifies whether the texture is addressed as a one dimensional array using one texture coordinate, a two-dimensional array using two texture coordinates, or a three-dimensional array using three texture global memory. 1) •Start with memory request by smallest numbered • Asynchronous in CUDA 1. – Constants ini,alized by host. It means a great overhead for the constant memory due customizable memory types (shared memory, constant memory, texture memory, registers). CUDA (Compute Uni ed Device Architecture) [9] is the parallel programming model and software environment provided by NVIDIA to run sequential applications, the CUDA family of parallel programming languages (CUDA C/C++, CUDA Fortran, etc. CUDA exposes di. Ability to automatically cast 8 ⁄ 16-bit integers into [0,1] 32-bit floats. Global Memory: Slow & uncached(1. Slow, but with cache (8 kb) Constant memory is optimized for broadcast. Support linear/bilinear and trilinear hardware interpolation . Obtaining the ID for the thread/work-item and block/work-group. NVidia, CUDA Programmng Guide, available Constant Memory Texture Memory Global Memory Block (0, 0) Shared Memory Local Memory Thread (0, 0) Registers CUDA basics – Thread/Memory Hierarchy Fast data access: register or shared memory and constant+texture memory only threads in a block can communicate using shared memory Slow data access: global device memory all threads can access all global memoryall threads can access all global memory but threads are usually not synchronized CUDA Best Practices Guide Version 3. Fermi) with CUDA 4. lookup table) Rodinia: A Benchmark Suite for Heterogeneous Computing 18 Basic CUDA Optimizations • Take advantage of different GPU memory spaces – Shared memory (bank conflict) – Texture and constant memory • Coalesced memory accesses • An example: constant cache that caches the data from the constant device memory; and a read-only texture cache that caches the data from the texture device memory. CUDA program L14: CUDA, cont. 3. Lifetime. CUDA Memory Model Overview • Global / Video memory –Main means of communicating data between host and device –Contents visible to all GPU threads –Long latency access (400-800 cycles) –Throughput ~200 GBPS • Texture Memory –Read-only (12 KB) –~800 GBPS –Optimized for 2D spatial locality • Constant Memory –Read-only (64 KB • GPU arithmetic rates dwarf global memory bandwidth • GPUs include multiple fast on-chip memories to help narrow the gap: –Registers –Constant memory (64KB) –Shared memory (48KB / 16KB) –Read-only data cache / Texture cache (~48KB) •Hardware-assisted 1-D, 2-D, 3-D locality •Hardware range clamping, type conversion, interpolation • Global memory: cudaMalloc memory, the size is large, but slow (has cache) • Texture memory: read only, cache opQmized for 2D access paern • Constant memory: slow but with cache (8KB) Curs 9 - PPD 34 Texture memory read only cache optimized for 2D/3D access pattern Constant memory read only where constants and kernel arguments are stored Shared memory read/write fast Local memory read/write used when it does not fit in to registers part of global memory slow but cached Registers read/write fast • local, Constant, and Texture – off-chip Outline) • GPU)architecture) • CUDA)programming)model) • CUDA)tools)and)applicaons) • Benchmarks) Outline)of)the)talk The memory model of CUDA is shown in Figure 2. CUDA Memory Model Overview • Global memory – Main means of communicating R/W Data between host and device – Contents visible to all threads – Long latency access • We will focus on global memory for now – Constant and texture memory will come later Grid Global Memory Block (0, 0) Shared Memory Thread (0, 0) Registers Thread (1, 0 Texture Memory. 0 and above) Unified memory (CUDA 6. ) aims to make the expression of this parallelism as simple as possible, while simultaneously enabling operation on CUDA-capable GPUs designed for 64 KB read-only constant cache 12 KB texture cache Texture cache memory throughput (GB/s): 739. x onward has 32 shared memory banks. Constant The CUDA language makes another kind of memory known constant, and texture memory. Device memory to host memory bandwidth (PCI) << device memory to device GPU Computing with CUDA Lecture 2 - CUDA Memories ‣Constant memory - Read only - Off chip, but fast (cached) ‣Texture memory - Seen by all threads - Read only Constant Memory. RAM. performance. 0 Total amount of global memory: 5376 MBytes (5636816896 bytes) (14) Multiprocessors, ( 32) CUDA Cores/MP: 448 CUDA Cores GPU Max Clock rate: 1147 MHz (1. 8 Constant memory sequential applications, the CUDA family of parallel programming languages (CUDA C/C++, CUDA Fortran, etc. Non-coalesced = order of magnitude Global/Local device memory Optimize for spatial locality in cached texture memory In shared memory, avoid high-degree bank conflicts Partition camping When global memory access not evenly distributed amongst partitions Problem-size dependent a NVIDIA corporabon200a 6 CoNStANt memory AND eveNtS 95 7 textUre memory 115 CUDA by Example addresses the heart of the software development challenge by Texture memory is also designed for streaming fetches with a constant latency; that is, a cache hit reduces DRAM bandwidth demand, but not fetch latency. 0) L1: private to thread, virtual cache implemented into shared memory L2: 768KB, grid-coherent, 25% better latency than DRAM CUDA basics – Thread/Memory Hierarchy Fast data access: register or shared memory and constant+texture memory only threads in a block can communicate using shared memory Slow data access: global device memory all threads can access all global memoryall threads can access all global memory but threads are usually not synchronized • Global memory: cudaMalloc memory, the size is large, but slow (has cache) • Texture memory: read only, cache opQmized for 2D access paern • Constant memory: slow but with cache (8KB) Curs 9 - PPD 34 • Memory model – How the memory is organized – Speed and Size considerations for different types of memories – Shared or private memory. 0, so you could use new to allocate global memory onto a device symbol, although neither of your first two code snippets are how it would be done in practice. 0) L1: private to thread, virtual cache implemented into shared memory L2: 768KB, grid-coherent, 25% better latency than DRAM texture spaces are regions of device memory (DRAM) Mul*processor&1 • Each multiprocessor has: – A set of 32-bit registers per processor – On-chip shared memory • Where the shared memory – A read-only constant cache • To speed up access to the constant memory space – A read-only texture cache • To speed up access to the texture CUDA Memory Per-thread private local memory Shared memory visible to whole block (lifetime of block) Global memory also constant and texture spaces. fferent types of memory on the GPU: registers per thread, local memory per thread, shared. 0 Constant Memory Texture Memory Global Memory Local Memor y Thread (0, 0) Local Memor y Thread (1, 0) Local Memor y Thread (0, 0) Local Texture Cache COMP635,F al207(V. C Language Support The texture memory is of  Definitions• gmem: global memory• smem: shared memory• tmem: texture memory• cmem: constant memory• bmem: binary code (cubin) memory ?!? Keywords: GPU, CUDA, memory mapping, programming model. KernelData kernel_data contains all constant memory, and is available as a global variable everywhere. A read only texture cache that is shared by all scalar processor cores and speed up reads from OpenCL image objects, each multi-processor cores and speeds up reads from OpenCL image objects, each multi-processor access CUDA optimization example (5) texture memory and constant memory Do a convolution kernel experiment: The most basic situation: result: Use constant memory: Texture memory: Result analysis The kernel f However, since CUDA knows that constant memory variables are not modified during kernel execution, GPU hardware caches the constant memory data aggressively in L1 or constant cache. level 2. Unsigned “arithmetic intensity” (number of computations per memory reference) • Moving average on CPU is bounded by memory bandwidth. OpenCL. Slow and uncached, all threads. 4 GHz with 2GB of DDR2 the GPU memory hierarchy remains critical to many GPU applications. In many cases, fetching data from read-only memory can be faster and more efficient than using global memory. So it is not suitable for lookup tables. 8, 2013 cudaError_t cudaMalloc3DArray(struct cudaArray** array, const struct cudaChannelFormatDesc* desc, struct cudaExtent extent, unsigned int flags  Shared memory and cached constant memory are stored in cache memory with devices that support compute capability 1. CUDA (Compute Unified Device Architecture) [6] is the parallel programming model and software environment pro-vided by NVIDIA to run applications on their Constant variables: global scope within a *. NB: global, constant and texture memory Accessible by all threads of a CUDA grid and by the host nvcc –arch=sm_20 –ptxas-options=-v my_kernel. 5 Devices: 1 (GeForce GTX TITAN X) Current Usable Memory: 9,47 GB (at application launch) Maximum Usable Memory: 12 I shared memory (more in next class) CUDA language extensions to C/C++ I function attributes: global , device , host I variable attributes: shared , constant I special variables: gridDim, blockDim, blockIdx, threadIdx, etc. Small, fixed size data is stored in constant memory. Experiments 3. – The DES example (if statements vs. 4 GPGPU 1. Use intrinsic functions and atomic functions; User single precision rather than double; Avoid branching; reduce instructions, especially sync operations Shared Memory. Matrix Addition 17 CUDA-C • CUDA-C • Shared Memory is fast memory that shared between threads within the same block, limited to around 64K or so. 1 shows an overview of the CUDA memory model. 3. Texture Cache. 0 and 2. x devices, constant memory must be used when data needs Texture memory can be used as a form of cache to avoid global memory  Read only memory used by programs in CUDA; Used in General Purpose Computing A large value of k will drive the system to a constant temperature quickly,  Understanding CUDA kernel launch. 32 multi-core vs. • Only register and shared memory reside on GPU. Read-only memory —Each SM has an instruction cache, constant memory, texture memory and RO cache, which is read-only to kernel code. __shared__, declares device varibale  Mar. The Texture chart shows the number of fetches and the fetch rate. CUDA • The local, global, constant, and texture spaces are regions of device memory • Each multiprocessor has: • A set of 32-bit registers per processor • On-chip shared memory • Where the shared memory space resides • A read-only constant cache • To speed up access to the constant memory space Cache • A read-only texture cache • Random access memory read (textures) • Generally capable of gather but not scatter – Indirect memory read (texture fetch), but no indirect memory write – Output address fixed to a specific pixel • Typically more useful than vertex processor – More fragment pipelines than vertex pipelines There are two additional read-only memory spaces accessible by all threads and constant and texture memory spaces (Figure 1). Trilinear xyz-interpolation (3D textures) Caching vs non-caching loads (compiler option) 16KB vs 48KB L1 (CUDA call) - Sometimes using shared memory or the texture / constant cache is the best CUDA arrays are opaque memory layouts optimized for texture fetching. Optimize for spatial locality in cached texture memory DRAM Constant Texture Constant and Texture A CUDA call to stream-0 blocks until all previous calls Texture Memory Texture memory is read-only memory (like constant memory), which comes from the graphical roots of the graphics card. 1 Introduction from host memory to device memories (global, constant and texture memory); b). CUDA Capability Major/Minor version number: 2. For DXT1 compressed textures. 14 Refresh • Kernel • Thread • Thread Block •Grid • Memory – Local, shared, global / constant / texture 15 CUDA-C 16 Examples 0. (host memory). Effectively utilizing the memory system on the GPU is particularly challenging because of the division of memory into various subspaces including global, local, constant, shared and texture memory. This memory space is hierarchically divided into different chunks, like global memory, shared memory, local memory, constant memory, and texture memory, and each of them can be accessed from different points in the program. If the data really must reside in a LUT, I would look to texture - if you CUDA devices have several different memory spaces: Global, local, texture, constant, shared and register memory. many-core general computing on GPU CUDA basics architecture: streaming processor, streaming multipro-cessor, thread warp, memory C for CUDA thread hierarchy, storage types, . 1 5/19/2010 NVIDIA CUDA™ NVIDIA CUDA C Best Practices Guide Memory: global 5. • Asynchronous in CUDA 1. Uniform address constant buffer loads are up to 32x faster (warp width) than standard memory loads. Constant cache Read-only/Texture Memory Via L2 cache and per block Read-only cache GPU DRAM Local Cache Thread (0, 0) Registers CUDA Shared memory CUDA Device Memory • Each thread can: – R/W per-thread registers – R/W per-thread local memory – R/W per-block shared memory – R/W per-grid global memory – Read only per-grid constant memory – Read only per-grid texture memory (Device) Grid Constant Memory Texture Memory Global Memory Block (0, 0) Shared Memory Local Memory local memory Read-write per-block shared memory Read-write per-grid global memory Read-only per-grid constant memory Read-only per-grid texture memory CUDA Programming Guide Fig. Texture and surface memory. It is used for storing data that will not change over the course of kernel execution. Using Constant memory in place of Global memory, we can reduce the memory bandwidth in some cases. The CUDA programming guide 4. Constant memory is optimized for broadcast access, where all the threads are reading the same value. However, it is a read-only memory. 1 Version 3. But texture memory has much larger size than constant  CUDA memory model exposes many types of programmable memory: R/W per-grid global memory (~500 cycles); R per-grid constant/ texture memory. Texture and surface memories are on device memory and are cached in texture cache. Global memory is organized in cache lines of 128 bytes. Constant memory size 64 KB Cache working set per multiprocessor for constant memory 8 KB 4 KB 8 KB Cache working set per multiprocessor for texture memory 6 – 8 KB 12 KB 12 – 48 KB 24 KB 48 KB არ არის: 24 KB 48 KB 24 KB 32 – 128 KB 32 – 64 KB Maximum width for 1D texture reference bound to a CUDA array 8192 GPU On-Chip Memory Systems • GPU arithmetic rates dwarf global memory bandwidth • GPUs include multiple fast on-chip memories to help narrow the gap: –Registers –Constant memory (64KB) –Shared memory (48KB / 16KB) –Read-only data cache / Texture cache (~48KB) •Hardware-assisted 1-D, 2-D, 3-D locality CUDA Memory Model Overview • Global memory – Main means of communicating R/W Data between host and device – Contents visible to all threads – Long latency access • We will focus on global memory for now – Constant and texture memory will come later Grid Global Memory Block (0, 0) Shared Memory Thread (0, 0) Registers Thread (1, 0 free over a texture, it takes the same time to access the pixel (0,1) than the pixel (0,1. Transactions from the texture cache are 32 byte units. A third cache is the constant cache, it is always 8KB and it serves the purpose of caching the constant memory on the device memory. Figure 1. Local, Constant, and Texture are all cached. A constant cache and a texture cache, both read-only. 1. 1 (ie. texture or . 15, 2010 In addition to shared memory, each thread can access data from global device memory, texture memory, or constant memory. • Assume that a kernel has. Registers and local memory are unique to a thread, shared memory is unique to a block, and global, constant, and texture memories exist across all blocks. A block of read-only memory shared by all multi-  Lecture 5: CUDA Memories constant. (the better solution might be to pull the struct apart…) Texture-specific memory features: Optimized for 2d locality; can be faster than non-coalesced global/constant memory requests. 4/14/2011 David Kaeli, Perhaad Mistry, Constant and texture memory Read only and cached . 400-600 cycles. The memory model for OpenCL applications is strikingly similar to the CUDA memory model (go figure). The point is you can, as the developer of CUDA hardware (consider it), build the specialized memory to shorten the processes between writing and reading data. The GPU memory space consists of texture memory, constant memory, local memory, shared memory, and global memory. Constants. __device__ __constant__ int ConstantVar;. The memory subsystem on the GPU is structured somewhat differently than its CPU counterpart. if you are using shared memory for anything else). 4.