HEBench
Vector Element-wise Addition Workload

Table of Contents

Operation Description

Summary

This operation is defined as:

C = op(A, B)

where

op(A, B) = A + B

is the standard vector element-wise addition.

Operation Parameters

Input: 2 parameters

Parameter Description
0 A is a vector with n components.
1 B is a vector with n components.

Result:

Output: 1 output

Output Description
0 C is a vector with n components. It is the result of adding A and B.

Details

If Z[i] denotes the element at component i in vector Z, then, the standard element-wise addition operation is defined as:

C[i] = A[i] + B[i]

Workloads

This document applies to the following workloads:

// From hebench/api_bridge/types.h
hebench:APIBridge::Workload::EltwiseAdd

Workload Parameters

Required workload parameters: 1

Index Name Type Description
0 n uint64_t Number of components in a vector.

Above parameters are required for the workload in the specified order. A backend must specify, at least, a set of default arguments for these parameters.

Backends can require extra parameters beyond the base requirements. If a backend requires extra parameters, these must have default values in every set of default arguments for the workload parameters.

Categories

This workload supports the following categories:

hebench:APIBridge::Category::Latency
hebench:APIBridge::Category::Offline

Category Parameters

Latency

See Latency Category .

Offline

See Offline Category .

Value ranges for elements in CategoryParams::offline::data_count. Default value is used when the backend implementation sets the data_count for the corresponding operand to 0, but user specified 0 or no value at run-time.

Parameter Lower bound Upper bound Default
0 1 none 5
1 1 none 5

Data Type

This workload is defined for the following data types:

hebench::APIBridge::DataType::Int32
hebench::APIBridge::DataType::Int64
hebench::APIBridge::DataType::Float32
hebench::APIBridge::DataType::Float64
hebench::APIBridge::WorkloadParamType::Float64
@ Float64
64 bits IEEE 754 standard floating point real numbers.
Definition: types.h:306
hebench::APIBridge::WorkloadParamType::Int64
@ Int64
64 bits signed integers.
Definition: types.h:304
hebench::APIBridge::Float32
@ Float32
32 bits IEEE 754 standard floating point real numbers.
Definition: types.h:382
hebench::APIBridge::Int32
@ Int32
32 bits signed integers.
Definition: types.h:380

Data Layout

All scalar elements in a vector with elements of type T (where T is any of the supported types) lie contiguous in memory.

For example, given the following vector A with n = 3 components:

A = [ a0, a1, a2 ]

The elements will be stored in memory as:

Offset: 0 1 2
A a0 a1 a2

Backends should expect this layout for their raw, clear text inputs, and must generate this layout for their decoded outputs.

Notes

If several vectors will be pointed at by a single pointer, consecutive vectors will follow each other in memory.

Dataset

Supported modes:

Generate External
yes yes

Data generation for vectors used as input for this workload occurs during workload initialization by Test Harness. Ground truths are pre-computed during data generation. There is no standard dataset.

During data generation, all vector elements are extracted from a pseudo-random uniform distribution between -10 and 10: u(-10, 10).