public static void Invoke(TSCudaContext context, CudaContext cudaContext, byte[] ptx, string baseName, params object[] args)
        {
            ThrowIfAnyTensorInvalid(args);

            cudaContext.SetCurrent();

            CudaDeviceProperties deviceInfo = context.DeviceInfoForContext(cudaContext);

            IEnumerable <Tensor> allTensors = args.OfType <Tensor>();
            Tensor firstTensor       = allTensors.First();
            long   elementCount      = firstTensor.ElementCount();
            ApplySpecialization spec = new ApplySpecialization(allTensors.ToArray());

            ConvertTensorArgs.Convert(cudaContext, spec.Use32BitIndices, args);

            ManagedCuda.VectorTypes.dim3 block = ApplyUtils.GetApplyBlock();
            ManagedCuda.VectorTypes.dim3 grid  = ApplyUtils.GetApplyGrid(deviceInfo, elementCount);

            string     fullKernelName = PermutationGenerator.GetMangledName(baseName, spec);
            CudaKernel kernel         = context.KernelCache.Get(cudaContext, ptx, fullKernelName);

            kernel.GridDimensions  = grid;
            kernel.BlockDimensions = block;
            kernel.RunAsync(CUstream.NullStream, args);
        }
Beispiel #2
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        /// <summary>
        /// Invokes the specified context.
        /// </summary>
        /// <param name="context">The context.</param>
        /// <param name="cudaContext">The cuda context.</param>
        /// <param name="ptx">The PTX.</param>
        /// <param name="baseName">Name of the base.</param>
        /// <param name="args">The arguments.</param>
        public static void Invoke(TSCudaContext context, CudaContext cudaContext, byte[] ptx, string baseName, params object[] args)
        {
            ThrowIfAnyTensorInvalid(args);

            var deviceInfo = context.DeviceInfoForContext(cudaContext);

            var allTensors   = args.OfType <NDArray>();
            var firstTensor  = allTensors.First();
            var elementCount = firstTensor.ElementCount();
            var spec         = new ApplySpecialization(allTensors.ToArray());

            ConvertTensorArgs.Convert(cudaContext, spec.Use32BitIndices, args);

            var block = ApplyUtils.GetApplyBlock();
            var grid  = ApplyUtils.GetApplyGrid(deviceInfo, elementCount);

            var fullKernelName = PermutationGenerator.GetMangledName(baseName, spec);
            var kernel         = context.KernelCache.Get(cudaContext, ptx, fullKernelName);

            kernel.GridDimensions  = grid;
            kernel.BlockDimensions = block;
            kernel.RunAsync(CUstream.NullStream, args);
        }
Beispiel #3
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        public static Tensor Invoke(CudaReduceAllKernels reduceAllKernels, float init, ReduceInitType initType, string kernelName, Tensor result, Tensor src, object extraArg = null)
        {
            int           deviceId    = CudaHelpers.GetDeviceId(src);
            TSCudaContext context     = CudaHelpers.TSContextForTensor(src);
            CudaContext   cudaContext = context.CudaContextForDevice(deviceId);

            if (src.DimensionCount > TSCudaContext.MaxDims)
            {
                throw new InvalidOperationException("Tensors with dimension count > " + TSCudaContext.MaxDims + " are not supported");
            }

            Tensor writeTarget = TensorResultBuilder.GetWriteTarget(result, src, false, 1);

            if (src.DimensionCount == 0)
            {
                return(result);
            }

            long totalElements         = src.ElementCount();
            ApplySpecialization config = new ApplySpecialization(src);
            object totalElementsTyped  = config.Use32BitIndices ? (uint)totalElements : (ulong)totalElements;
            object initValueTyped      = ReduceInitConverter.GetInitValue(init, initType, src.ElementType);

            dim3 grid;
            dim3 block;

            byte[] ptx            = reduceAllKernels.GetPtx(context.Compiler);
            string fullKernelName = PermutationGenerator.GetMangledName(kernelName, config);

            ManagedCuda.BasicTypes.CUdeviceptr outputDevicePtr = CudaHelpers.GetBufferStart(writeTarget);

            if (isTwoPassReductionSize(totalElements))
            {
                getPass1ReduceBlockGrid(context, deviceId, totalElements, out grid, out block);
                uint smemSize = block.x * sizeof(float);

                ManagedCuda.BasicTypes.CUdeviceptr scratchSpace = context.ScratchSpaceForDevice(deviceId).buffer;

                if (extraArg == null)
                {
                    InvokeReduceAll(context, cudaContext, ptx, "twoPassA_" + fullKernelName, grid, block, smemSize, config, src, totalElementsTyped, initValueTyped, scratchSpace);
                }
                else
                {
                    InvokeReduceAll(context, cudaContext, ptx, "twoPassA_" + fullKernelName, grid, block, smemSize, config, src, totalElementsTyped, initValueTyped, scratchSpace, extraArg);
                }

                uint numPass1Blocks = grid.x;
                getPass2ReduceBlockGrid(context, deviceId, totalElements, out grid, out block);
                smemSize = block.x * sizeof(float);

                InvokeReduceAllPass2(context, cudaContext, ptx, "twoPassB_" + fullKernelName, grid, block, smemSize, config.Use32BitIndices, numPass1Blocks, initValueTyped, scratchSpace, outputDevicePtr);
            }
            else
            {
                getSinglePassReduceBlockGrid(totalElements, out grid, out block);
                uint smemSize = block.x * sizeof(float);

                if (extraArg == null)
                {
                    InvokeReduceAll(context, cudaContext, ptx, "onePass_" + fullKernelName, grid, block, smemSize, config, src, totalElementsTyped, initValueTyped, outputDevicePtr);
                }
                else
                {
                    InvokeReduceAll(context, cudaContext, ptx, "onePass_" + fullKernelName, grid, block, smemSize, config, src, totalElementsTyped, initValueTyped, outputDevicePtr, extraArg);
                }
            }

            return(writeTarget);
        }
Beispiel #4
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        public static Tensor Invoke(CudaReduceKernels reduceKernels, string kernelName, float init, ReduceInitType initType, Tensor result, Tensor src, int dim, object extraArg = null)
        {
            if (src.DimensionCount == 0)
            {
                return(result);
            }

            var context     = CudaHelpers.TSContextForTensor(src);
            var cudaContext = context.CudaContextForTensor(src);

            var requiredOutputSize = (long[])src.Sizes.Clone();

            requiredOutputSize[dim] = 1;
            var writeTarget = TensorResultBuilder.GetWriteTarget(result, src, false, requiredOutputSize);

            ThrowIfAnyTensorInvalid(writeTarget, src);

            var inElements      = src.ElementCount();
            var reductionSize   = src.Sizes[dim];
            var reductionStride = src.Strides[dim];
            var outElements     = inElements / reductionSize;
            var contigReduction = reductionStride == 1;


            // We must make sure that when the tensor is passed to the kernel, src.Sizes[dim] is set to 1
            // This includes for the purposes of determining which tensor specializations to use (changing
            // the dimension size to 1 may make the tensor non-contiguous
            var newSizes = (long[])src.Sizes.Clone();

            newSizes[dim] = 1;
            var srcSlim = new Tensor(newSizes, src.Strides, src.Storage, src.StorageOffset);

            var    config               = new ApplySpecialization(writeTarget, srcSlim);
            object totalSlices          = config.Use32BitIndices ? (uint)outElements : (ulong)outElements;
            object reductionSizeTyped   = config.Use32BitIndices ? (uint)reductionSize : (ulong)reductionSize;
            object reductionStrideTyped = config.Use32BitIndices ? (uint)reductionStride : (ulong)reductionStride;
            var    initValueTyped       = ReduceInitConverter.GetInitValue(init, initType, src.ElementType);

            var ptx = reduceKernels.GetPtx(context.Compiler);

            if (contigReduction)
            {
                var block    = GetContigReduceBlock(cudaContext, outElements, reductionSize);
                var grid     = GetContigReduceGrid(outElements);
                var smemSize = (uint)src.ElementType.Size() * block.x;

                var fullName = "contig_" + PermutationGenerator.GetMangledName(kernelName, config);
                if (extraArg == null)
                {
                    InvokeReduce(context, cudaContext, ptx, fullName, grid, block, smemSize, config, writeTarget, srcSlim, reductionSizeTyped, totalSlices, initValueTyped);
                }
                else
                {
                    InvokeReduce(context, cudaContext, ptx, fullName, grid, block, smemSize, config, writeTarget, srcSlim, reductionSizeTyped, totalSlices, initValueTyped, extraArg);
                }
            }
            else
            {
                var  deviceProps = context.DeviceInfoForContext(cudaContext);
                var  block       = GetNonContigReduceBlock(deviceProps);
                var  grid        = GetNoncontigReduceGrid(deviceProps, outElements);
                uint smemSize    = 0;

                var fullName = "noncontig_" + PermutationGenerator.GetMangledName(kernelName, config);
                if (extraArg == null)
                {
                    InvokeReduce(context, cudaContext, ptx, fullName, grid, block, smemSize, config, writeTarget, srcSlim, reductionStrideTyped, reductionSizeTyped, totalSlices, initValueTyped);
                }
                else
                {
                    InvokeReduce(context, cudaContext, ptx, fullName, grid, block, smemSize, config, writeTarget, srcSlim, reductionStrideTyped, reductionSizeTyped, totalSlices, initValueTyped, extraArg);
                }
            }

            return(writeTarget);
        }