clclj_example.clj

(ns com.ndensity.clclj.example
  (:require [com.ndensity.clclj :as clclj :refer [clfn]]))

(defn cube [n] ; if you don't type hint, it assumes int32 for all args & return types
  (* n n n))
(def cube_cl (clfn* cube))

(def square-cl
  (clfn [n]
    (let [a (inc n)
          b (- n 5)]
      ;; If you return a vector, it'll be typed as an int32 array
      [(* (b + a) n n) (* n n) (clclj/cl* "a*a") (clclj/call :cube_cl n)])))

(def cube-elems-cl
  (clfn [n-vec]
    (clclj/clfor-map :cube_cl n-vec))) ;; this restructures the map statement into a for statement in OCL

;; Easy data parallelism
(def res1 (clclj/map square-cl (range 40))) ;; By default, will choose "best context"
(def res2 (clclj/map square-cl (clclj/wrap (range 40) :int32)
                     :context (first (clclj/available-gpu-devices))))
(def res3 (clclj/map square-cl (vec (range 40))
                     :context (first (clclj/available-cpu-devices))))
;; Support for all of the functions found in core.reducers

;; Easy task parallelism
(def res4 (clclj/data-map [1 2 3 4] (repeat 10 cube-elems-cl)))

;; * jBLAS for OCL via JavaCL
;; * incanter-core that uses the OCL jBLAS
;; * all other JavaCL goodies

Hey, cool, I was going to ask if you went ahead and did this without me. Is there a repo anywhere?